--- title: Databricks Reviews meta_title: 'Databricks Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 1349 reviews by the users' company size, role or industry to find out how Databricks works for a business like yours. aggregate_rating: rating_value: 4.6 review_count: 1349 scale: '5' date_modified: '2026-07-21' parent_category: name: Big Data url: https://www.g2.com/categories/big-data --- # Databricks Reviews **Vendor:** Databricks Inc. **Category:** [Big Data Processing And Distribution Systems](https://www.g2.com/categories/big-data-processing-and-distribution) **Average Rating:** 4.6/5.0 **Total Reviews:** 1,349 ## About Databricks Databricks is a unified data and AI platform that helps organizations build, govern and scale data pipelines, analytics, machine learning, AI applications and agents. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on Databricks to work with enterprise data and AI at scale. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Agent Bricks, Lakeflow, Lakehouse, Lakebase, Genie and Unity Catalog. Founded in 2013 by the original creators of Apache Spark™, Delta Lake, MLflow and Unity Catalog, Databricks is built on an open lakehouse architecture that brings data, analytics and AI together. The platform is used by data engineers, data scientists, analysts, developers, machine learning teams, AI teams and business users to collaborate across the full data and AI lifecycle. Key Databricks capabilities include: - Data engineering: Build, automate and manage reliable batch, streaming and real-time data pipelines. - Analytics and business intelligence: Run SQL analytics, create dashboards and enable business teams to explore data. - Data governance: Discover, secure and manage data and AI assets across teams, clouds and workloads. - Machine learning and AI: Develop models, build generative AI applications and create production-grade AI agents. - Data applications: Build and deploy data-driven applications using governed enterprise data. Available across AWS, Azure and Google Cloud, Databricks helps organizations work across clouds, reduce data silos and simplify collaboration across teams and tools. Customers use Databricks for use cases such as customer personalization, fraud detection, predictive maintenance, real-time analytics, cybersecurity, healthcare research, financial risk management, supply chain optimization and AI-powered decision-making. Databricks is used across industries including financial services, healthcare and life sciences, retail, manufacturing, energy and the public sector. Organizations use the platform to modernize data infrastructure, accelerate AI adoption and turn enterprise data into business value. ## Databricks Pros & Cons **What users like:** - Users praise the **ease of use** and **comprehensive features** of Databricks for data warehousing and ML applications. (192 reviews) - Users praise the **ease of use** of Databricks, enhancing their experience with intuitive interfaces and reliable services. (154 reviews) - Users appreciate the **seamless integrations** of Databricks with AWS and other tools, enhancing daily operations and efficiency. (141 reviews) - Users value the **seamless collaboration** offered by Databricks, enhancing teamwork on data projects with real-time insights. (114 reviews) - Users praise the **integrated analytical features** of Databricks, enhancing collaborative data processing and insight visualization. (112 reviews) - Scalability (111 reviews) - ML Integration (106 reviews) - Users appreciate the **easy integrations** of Databricks, seamlessly connecting with cloud infrastructure and enhancing data management. (102 reviews) - Machine Learning (97 reviews) - Users value the **effective data management features** of Databricks, simplifying their workflows and enhancing decision-making. (87 reviews) **What users dislike:** - Users note a **steep learning curve** initially, with confusing permissions and compute modes affecting usability. (78 reviews) - Users note that the **costs can be quite high** for utilizing Databricks effectively, especially for large data projects. (71 reviews) - Users find a **steep learning curve** with Databricks, especially challenging for newcomers to big data tools. (64 reviews) - Users find the **complexity** of Databricks challenging, especially for smaller teams and initial setup processes. (45 reviews) - Users face **complex setup** challenges initially, though support helps simplify the experience over time. (35 reviews) - Performance Issues (34 reviews) - Users face **unintuitive UI issues** that lead to random errors and complicate the experience for non-technical users. (34 reviews) - Poor UI Design (33 reviews) - Users express frustration over **missing features** in Databricks, limiting its effectiveness for complex deployments and custom setups. (31 reviews) - Cost (29 reviews) ## Databricks Reviews ### 1. Empowers Collaborative Data Science with Minor Learning Curve **Rating:** 4.5/5.0 stars **Reviewed by:** Arman M. | Software Developer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** April 01, 2026 **What do you like best about Databricks?** I use Databricks for a lot of things. The main ones are making sense out of the data, looking at chunks of data, and doing machine learning. Databricks makes these tasks very easy and helpful, especially for data projects. It's great for collaborating with friends and developing my Python code in notebooks. I like Databricks because it has good capabilities for handling big data and is excellent for working with the data and machine learning. It's also easy to use when working with people, as many can work on a project and share their findings. **What do you dislike about Databricks?** Databricks is very powerful, but there are some things that need improvement. It's hard to learn for beginners when working with Spark and setting up clusters, as this was confusing at first. Sometimes the interface and settings can feel complicated. I think it would be helpful if there were clear setup instructions so new users could get started easily with Databricks. **What problems is Databricks solving and how is that benefiting you?** I use Databricks to make sense of data, collaborate with others, and develop Python code. It simplifies data engineering, machine learning, and handling data while allowing multiple people to work on notebooks simultaneously. **Official Response from Janelle Glover:** > Thank you for sharing your positive experiences with Databricks, including its capabilities for handling big data and machine learning. We understand the challenges of learning to work with Spark and setting up clusters, and we are committed to enhancing our resources to make the onboarding process smoother for beginners. ### 2. Versatile Platform with Robust Data Governance **Rating:** 4.5/5.0 stars **Reviewed by:** Harthika S. | Senior Data Engineer, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** March 31, 2026 **What do you like best about Databricks?** I personally like the Databricks UI, especially the dark mode. Technically, I find Unity Catalog's built-in lineage and governance very valuable. Auto-loader's incremental file processing with exactly-once guarantees and Delta Lake's ACID reliability are my personal favorites. Delta Lake's ACID transactions ensure our data pipelines either fully succeed or fully roll back, which prevents partial writes from corrupting tables. Time travel in Delta Lake allows us to query previous versions of our table for audits without needing separate snapshots. Unity Catalog's capability to auto-track lineage across our entire pipeline is critical for regulatory audits, and its role-based access control and column masking ensure data access is properly managed across teams. The workspace and notebook setup were straightforward, making the initial setup relatively easy. **What do you dislike about Databricks?** Migrating from hive_metastore to Unity Catalog is painful with limited tooling - UCX helps but it's still a heavy lift. Databricks-to-dbt cloud orchestration lack a clean native handoff, forcing custom API polling code that's fragile and hard to debug. Cost visibility for Serverless SQL warehouse could be more granular - it's hard to attribute DBU spend to specific pipelines or dbt models without digging into system tables manually. **What problems is Databricks solving and how is that benefiting you?** Databricks replaced our fragmented data stack with one platform for ingestion, ETL, analytics, and governance. Unity Catalog handles regulatory lineage needs by auto-tracking data provenance. **Official Response from Janelle Glover:** > Thank you for sharing your positive experience with Databricks! We're glad to hear that you find the UI, Unity Catalog, and Delta Lake features valuable for your data governance and reliability needs. ### 3. An all-in-one platform **Rating:** 4.0/5.0 stars **Reviewed by:** Pang L. | Machine Learning Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** March 18, 2026 **What do you like best about Databricks?** It's an all-in-one platform for data engineers, analysts, data scientists, and business users. **What do you dislike about Databricks?** It’s easy to overspend and it is a vendor lock-in. **What problems is Databricks solving and how is that benefiting you?** Data engineering, model training and inference, GenAI. Databricks solves the problem of having fragmented tools across the data and AI lifecycle. Traditionally, teams would need separate platforms for data engineering, analytics, machine learning, and AI — leading to silos, duplicated work, and governance challenges. With Databricks, data engineering pipelines, model training and inference, and GenAI development all live in one unified environment. This means data engineers can build and orchestrate pipelines, data scientists can train and deploy models, and teams can develop and serve GenAI applications — without constantly moving data or context-switching between tools. **Official Response from Janelle Glover:** > Thank you for sharing the specific problems that Databricks is solving for you. We are committed to streamlining the data and AI lifecycle to eliminate silos, duplicated work, and governance challenges. ### 4. Effortless ETL and Governance with Databricks **Rating:** 5.0/5.0 stars **Reviewed by:** Vivek N. | Small-Business (50 or fewer emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I use Databricks for ETL, jobs, and streaming applications, and I appreciate its faster, reliable ingestion and proper data governance. It's easier to build ETL jobs and pipelines with Databricks and have a unified governance. I find Autoloader with Unity Catalog particularly helpful. Databricks is also easy to maintain, and it allows for high-speed ingestion without data loss, with less maintenance. The initial setup was easy, which is a big plus. **What do you dislike about Databricks?** Nothing **What problems is Databricks solving and how is that benefiting you?** I use Databricks for faster, reliable ingestion and proper data governance. It makes building ETL jobs and pipelines easier and has a unified governance. Autoloader with Unity Catalog helps maintain high-speed ingestion without data loss and requires less maintenance. **Official Response from Janelle Glover:** > Thank you for sharing your positive experience with Databricks! We're delighted to hear that our platform has made building ETL jobs and pipelines easier for you, while also providing unified governance and high-speed ingestion. We appreciate your feedback and look forward to continuing to support your data needs. ### 5. Unifies Data Processing with Delta Lake's Reliability **Rating:** 5.0/5.0 stars **Reviewed by:** Tan Suong N. | Cloud Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** March 29, 2026 **What do you like best about Databricks?** I use Databricks in my enterprise environment and projects to ingest data from multiple sources, transform and clean it at scale, and prepare reliable datasets for analytics and reporting. It allows me to build and manage data pipelines efficiently using Spark, SQL, and notebooks. I love having data ingestion, large-scale processing, analytics, and collaboration all in one place, making my workflow much more streamlined and efficient. I really value the reliability and confidence I get from features like Delta Lake, which make data versioning, recovery, and handling changes much safer, cheaper, and easier in my projects. Delta Lake is one of the main reasons Databricks is so valuable to me because it directly addresses reliability and trust, which are constant challenges in real data projects. The ability to rollback to a previous version if something goes wrong makes me much more confident when developing, testing, or deploying changes to production pipelines. Additionally, the initial setup was relatively straightforward because Databricks integrates well with our existing cloud infrastructure. **What do you dislike about Databricks?** The learning curve can be quite steep at the beginning, especially for users who are new to Spark or large scale data processing concepts. Debugging complex pipelines or job failures can sometimes be time-consuming, when error messages are not very intuitive. As workflows and environments grow, governance and environment management can require extra effort to keep everything well-organized and consistent. Cost management is another challenge, as resource usage can increase quickly if clusters and jobs are not configured or monitored carefully. **What problems is Databricks solving and how is that benefiting you?** I use Databricks to solve fragmentation and inefficiency in my data flow, handling ingestion, transformation, analytics, and collaboration on one platform. It reduces operational overhead, ensures data quality, and offers scalability, improving large data processing without infrastructure worries. **Official Response from Janelle Glover:** > Thank you for sharing your positive experience with Databricks! We're glad to hear that our platform has helped streamline your workflow and provide reliability and confidence in your data projects. We understand the challenges with the learning curve and debugging, and we're continuously working to improve user experience and provide better error messaging. We appreciate your feedback and are committed to addressing these challenges. ### 6. Scalable, Unified Platform with a Steep Learning Curve **Rating:** 4.5/5.0 stars **Reviewed by:** Nitin P. | Mid-Market (51-1000 emp.) **Reviewed Date:** March 29, 2026 **What do you like best about Databricks?** I use Databricks for my office projects, and I really like its ability to unify the entire data workflow in a single platform. It lets me seamlessly collaborate with data scientists and analysts, making it easy to ingest, clean, analyze, and model data. I appreciate its scalability and automation features, which save me time and reduce complexity when working with large datasets. I also like that it offers a scalable compute and storage solution, reducing infrastructure management overhead. The integration of shared notebooks and tools like Databricks Genie helps improve collaboration and speed up development. **What do you dislike about Databricks?** I haven't faced major issues with Databricks itself, but during my initial phase of using the platform, it wasn't very easy to get up to speed with all the features, tools, and configurations. Databricks evolves quickly and in the beginning, it was a bit challenging to match the pace of updates and fully leverage all its capabilities. The initial setup was moderately challenging. While the platform is well documented and user-friendly, getting familiar with all the features, configuring clusters and integrating it with our existing workflows required some learning and experimentation. **What problems is Databricks solving and how is that benefiting you?** Databricks solves scalability and performance issues, centralizing data from multiple sources and reducing silos. It simplifies collaboration among data professionals, offers scalable compute, and integrates advanced analytics, saving time and reducing complexity with large datasets. **Official Response from Janelle Glover:** > It's great to hear that Databricks and Genie have been beneficial in centralizing data and improving collaboration for your team. We understand that the initial setup and learning curve can be challenging, and we are continuously working to address these concerns. ### 7. Versatile Data Platform with Seamless Integration **Rating:** 4.0/5.0 stars **Reviewed by:** Ayobami A. | Senior Consultant - BI, Data & Analytics, Enterprise (> 1000 emp.) **Reviewed Date:** March 28, 2026 **What do you like best about Databricks?** What I like most about Databricks is that it's integratable with other platforms. I can literally set up a Databricks workspace using Azure data services from the Azure portal, and I can also use Databricks within AWS. It gives me the opportunity to integrate my Databricks notebooks into other environments and orchestration tools or ETL tools, like Azure Data Factory. **What do you dislike about Databricks?** For now, I noticed when I'm using Azure Databricks, particularly the Azure Databricks cluster, it usually times out, and it's kind of frustrating for me. Most times when I'm working, I just go into another tab. Every time I come back in a minute or two, it's timed out, and I have to sign in again. That experience can be frustrating. I would like that to be looked into. I don't know if it's an issue with Databricks or if it's an issue from the Azure side from the intraident authentication part of things. **What problems is Databricks solving and how is that benefiting you?** I use Databricks to unify my data by managing governance within the Unity catalog, simplifying user access and report sharing. **Official Response from Janelle Glover:** > It's fantastic to hear that Databricks is helping you unify your data, manage governance within the Unity catalog, and simplify user access and report sharing. We apologize for the frustration you've experienced with the Azure Databricks cluster timing out. Can you please contact our team via www.databricks.com/support so we can help look into this further? Thank you! ### 8. Lakehouse + Unity Catalog + DLT: Unified Governance and Efficient, Scalable Pipelines **Rating:** 5.0/5.0 stars **Reviewed by:** Héttori T. | Enterprise (> 1000 emp.) **Reviewed Date:** June 17, 2026 **What do you like best about Databricks?** The Lakehouse architecture beautifully unifies data warehousing and data lakes. Unity Catalog simplifies governance across the board, and Delta Live Tables (DLT) makes building and monitoring robust, scalable production pipelines incredibly efficient. **What do you dislike about Databricks?** The DBUs cost model can scale rapidly and become quite expensive if cluster policies and auto-scaling boundaries are not strictly monitored and optimized. Budget governance requires constant attention. **What problems is Databricks solving and how is that benefiting you?** Databricks solves the challenge of data siloization by merging data warehousing and data lakes into a single Lakehouse architecture. For me, this eliminates the need to maintain separate storage and compute systems for BI and AI, significantly reducing data duplication and architectural complexity while ensuring centralized governance via Unity Catalog. **Official Response from Janelle Glover:** > Thank you for sharing your positive experience with Databricks, especially the benefits of the Lakehouse architecture, Unity Catalog, and Delta Live Tables. We understand the challenges related to the DBUs cost model and the importance of monitoring and optimizing cluster policies. We're committed to helping our customers effectively manage costs while maximizing the value of our platform. ### 9. Streamlined DevOps with Enhanced Production Speeds **Rating:** 5.0/5.0 stars **Reviewed by:** Adrian P. | Business Development Executive, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I really like the UI, the product itself, and the library that Databricks offers. The conference I'm at now is also great. Our development team has benefitted as it has increased production speeds and minimized working on too many meticulous items. **What do you dislike about Databricks?** When it comes to products, when it comes to community Postgres. They have more integration. I know they have some fake base right now that they came out with. More products when it comes to Postgres. Or extensions that are themed around that'd be awesome. **What problems is Databricks solving and how is that benefiting you?** Databricks solves my infrastructure problems, making automation and working with DevOps easier. It helps increase production speeds and minimizes the effort on meticulous tasks. **Official Response from Janelle Glover:** > We're glad to hear that you are enjoying the UI, product, and library offered by Databricks, as well as the benefits it has brought to your development team's productivity. ### 10. Databricks Unifies Data Engineering, Science, and Analytics Exceptionally Well **Rating:** 5.0/5.0 stars **Reviewed by:** Naveena P. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** March 27, 2026 **What do you like best about Databricks?** The ability to converge data engineering, data science, and analytics on a single platform without compromising on governance, performance, or flexibility is still rare in the industry. Databricks executes this exceptionally well. **What do you dislike about Databricks?** Reducing the spinning time of all purpose clusters and job clusters. It would be more usefula nd helpful if it starts as quick as serverless **What problems is Databricks solving and how is that benefiting you?** In enterprise banking, where regulatory compliance, data accuracy, and operational resilience are non-negotiable, Databricks is solving some of our most critical challenges. As a Lead Data Engineer managing end-to-end ETL pipelines, dashboard delivery, monitoring alerts, and data governance for a major banking client, the platform has become the backbone of our modern data architecture. Databricks unifies our fragmented data landscape through Delta Lake and Unity Catalog, giving us ACID-compliant transactions for reliable ETL, automated lineage for audit-ready governance, and fine-grained access controls to protect sensitive PII and financial data—all while enabling seamless schema evolution to handle the constant changes in source systems. This directly translates to faster, more trustworthy reporting: our dashboards in Power BI and Tableau now pull from a single source of truth, eliminating metric disputes between Risk, Finance, and Compliance teams. On the operational side, native alerting integrated with Slack and PagerDuty, combined with Databricks System Tables for observability, lets us proactively catch data quality issues or SLA breaches before they impact business decisions—reducing incident resolution time by over 60%. Ultimately, Databricks isn't just improving our engineering efficiency; it's enabling us to innovate responsibly in a highly regulated environment, delivering trusted insights at scale while keeping auditors confident and stakeholders aligned. **Official Response from Janelle Glover:** > Thank you for sharing your positive experience with Databricks! We're glad to hear that our platform is helping you unify data engineering, science, and analytics while maintaining governance, performance, and flexibility. ### 11. Comprehensive Platform with Room for Improvement **Rating:** 4.0/5.0 stars **Reviewed by:** Sathya R. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** March 27, 2026 **What do you like best about Databricks?** I find Databricks to be a one-stop solution because it incorporates various functionalities such as orchestrating pipelines. It also has an inbuilt AI called Genie, which helps in building jobs, and other AI-related tasks. I appreciate that compared to other providers like AWS and Azure, Databricks offers specific features that they lack, allowing me to use the database simply and access everything in one place. The initial setup was quite easy because I could use a single stop to directly implement and update tables using the data lakehouse, which is easier compared to others **What do you dislike about Databricks?** I think Databricks could improve on the orchestration part. Even though it has orchestration capabilities for pipelines and jobs, it misses the ease of access that something like Airflow provides, which is specifically designed for orchestration. It would be helpful if Databricks adopted a pattern similar to Airflow's for better orchestration and job linking. I also feel the Genie part could be improved. While the Genie works well, the output duration can be lengthy, usually taking more than five to ten minutes to perform specific tasks. So, I would like to see improvements in that area as well. **What problems is Databricks solving and how is that benefiting you?** I use Databricks as a one-stop solution for various tasks. It orchestrates pipelines and utilizes an inbuilt AI, making it more feature-rich than alternatives like AWS or Azure. This allows me to streamline workflows without relying on multiple providers. **Official Response from Janelle Glover:** > Thank you for sharing your feedback on Databricks. We're glad to hear that you find our platform to be a comprehensive solution with valuable functionalities such as Genie. We appreciate your input on areas for improvement and will take your suggestions into consideration for future updates. ### 12. Seamless Integration, Needs Performance Tuning **Rating:** 4.0/5.0 stars **Reviewed by:** Pandi A. | Lead Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** March 27, 2026 **What do you like best about Databricks?** I think the most useful part of Databricks is its single architecture where you can have everything, like a database and dashboard, all in one. Compared to other providers like Azure or AWS, where I would need multiple services, Databricks offers everything in a single service. This simplifies my work because I don't have to manage integration or network level details across different services. The convenience of having everything inside Databricks means I can avoid multiple network updates when connecting with tools like Power BI, which makes it a standout feature for me. Additionally, the initial setup after migrating from Snowflake was pretty easy since Databricks allows us to manage access and security within a single service. **What do you dislike about Databricks?** Yeah, so one thing that needs to be updated is Genie code. If I look at it, Genie code is helpful for generating code but when it does in the back end, it consumes much memory. For example, if I'm opening Databricks in Chrome, it's gonna take at least one or two GB memory at the back end, and that takes a lot of time to generate the response as well. So if we could reduce that, it would be great. Also, on the pipeline stuff, for example, if you take Airflow, Airflow is specifically designed for our position. We use Airflow and I can see, for example, if I have thousands of jobs, I can see each and every job and what's happening. But with Databricks, it's a tough job for me to see the success and failures and to manage the charts. We have multiple options to monitor it in Databricks, but it's hard when compared with Airflow. **What problems is Databricks solving and how is that benefiting you?** Databricks helps us consolidate data from different locations into a single database, simplifying master data management and making data access easier with integrated dashboards, improving our AI-powered sales and prospect tracking. **Official Response from Janelle Glover:** > Thank you for taking the time to provide your feedback. We're pleased to hear that Databricks has helped simplify your data management and improve your AI-powered sales and prospect tracking. We have noted your feedback on Genie and pipeline management, and we will explore ways to enhance these features for a better user experience. ### 13. Databricks: A Unified, Scalable Platform for Faster Collaboration and Innovation **Rating:** 5.0/5.0 stars **Reviewed by:** Jananisree T. | Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** March 27, 2026 **What do you like best about Databricks?** Databricks stands out because it provides a unified platform that seamlessly combines data engineering, machine learning, and analytics, making collaboration across teams much easier. I especially appreciate how it simplifies working with big data by integrating with popular tools like Apache Spark, offering scalability, and enabling faster experimentation. The collaborative notebooks, strong support for multiple programming languages, and built-in security features make it both powerful and user-friendly. Overall, it helps accelerate innovation by reducing complexity and improving productivity across the entire data lifecycle. **What do you dislike about Databricks?** One drawback of Databricks is that it can feel overwhelming for new users because of its complexity and steep learning curve. The platform offers a wide range of powerful features, but navigating them effectively often requires significant technical expertise. Additionally, costs can escalate quickly if clusters are not managed carefully, and performance tuning sometimes demands deep knowledge of Spark internals. Integration with certain external tools can also be less seamless compared to other platforms. **What problems is Databricks solving and how is that benefiting you?** Databricks is solving the challenge of managing and analyzing massive amounts of data by providing a unified platform for data engineering, machine learning, and analytics. It eliminates the need to juggle multiple tools, making workflows more streamlined and collaborative. For me, this means faster access to insights, easier experimentation with models, and reduced complexity in handling big data. The benefit is clear: improved productivity, better collaboration across teams, and quicker decision-making powered by reliable data. **Official Response from Janelle Glover:** > We appreciate your feedback on the benefits of using Databricks for managing and analyzing massive amounts of data. It's great to hear that our platform has contributed to improved productivity, easier experimentation with models, and better collaboration across teams. We acknowledge the challenges with the learning curve and cost management, and we're dedicated to addressing these concerns to better serve our users. ### 14. Unified Lakehouse Architecture for ETL, Analytics, and ML in One Stack **Rating:** 4.5/5.0 stars **Reviewed by:** Charumathi A. | Technical Lead- Data Engineering, Enterprise (> 1000 emp.) **Reviewed Date:** March 27, 2026 **What do you like best about Databricks?** Unified lakehouse architecture: Databricks lets me treat my data lake more like a “lakehouse,” combining data-lake flexibility with data-warehouse-like features such as ACID transactions, schema enforcement, and time travel on Delta tables. As a result, I can handle ETL, ad hoc analytics, and ML on a single stack, rather than juggling separate warehouses, lakes, and Spark clusters. **What do you dislike about Databricks?** The platform can feel heavy and is sometimes slow, especially when working with large notebooks or running long jobs. Databricks can also be expensive to operate, particularly if clusters are left idle or aren’t well optimized. **What problems is Databricks solving and how is that benefiting you?** Faster, collaborative workflows Databricks simplifies big-data complexity by abstracting much of the Spark and cluster management, so I can focus more on logic and less on infrastructure. The built-in notebooks, jobs, and versioning make it easy to prototype quickly, collaborate with analysts and DS, and move code from experimentation into production with less rework. Unified platform for data and AI Databricks reduces the need for separate data-lake, data-warehouse, and ML tools by providing a single lakehouse platform where you can store, transform, and analyze data, and run ML workloads in the same place. This helps cut down on tool sprawl and makes it easier to share data and models across engineering, analytics, and data science teams. **Official Response from Janelle Glover:** > Thank you for sharing what you like best about Databricks! We appreciate your feedback and are continuously working on improving performance and optimizing costs to provide a better experience for our users. ### 15. Simplifies Data Engineering, Needs Better Tool Integration **Rating:** 4.0/5.0 stars **Reviewed by:** Aladdin A. | Senior Solutions Engineer - Cloud & AI Data, Mid-Market (51-1000 emp.) **Reviewed Date:** March 26, 2026 **What do you like best about Databricks?** I like the features of Genie, especially the new junior code, which makes it possible to get SQL-ready scripts by just chatting using natural language. This is fascinating, especially with the governance layer on top of it with Unity. It accelerates both analysts' and engineers' jobs by helping build reports and getting them ready efficiently, especially since it has access to most of the metadata. The documentation is also useful, suggesting SQL code that can be provisioned on the fly. Tying Genie with AI functions such as the ai_query makes it a superpower. **What do you dislike about Databricks?** Honestly, a ton of features that can be improved, especially connectivity with other tools, such as cloud tools, especially like Azure. As a Microsoft employee, I evangelize Databricks, but many of our clients use the Microsoft stacks extensively. Sometimes, these tools feel isolated from the whole stack. There’s still a lot of work to be done to connect models provisioned in Azure and things like unity catalogs or governance that can sit outside of Databricks and Microsoft's stack. This feels like a disconnect, especially in highly regulated environments where on-prem stuff needs to interact with Databricks capabilities. **What problems is Databricks solving and how is that benefiting you?** Databricks simplifies provisioning services, streamlines data engineering, and speeds up workflow creation. It combines tools into one governed platform, making handling big data easier and faster. Its AI layer integrates well, reducing the need for multiple tools. **Official Response from Janelle Glover:** > We're glad to hear that you are enjoying the features of Genie. We understand your concerns about the connectivity with other tools, especially Azure, and we are continuously working to improve integrations to provide a seamless experience across different platforms. ### 16. Outstanding Experience with This Software **Rating:** 4.0/5.0 stars **Reviewed by:** Kriti K. | CFO, Mid-Market (51-1000 emp.) **Reviewed Date:** January 09, 2026 **What do you like best about Databricks?** Databricks data intelligence is a platform that helps in accommodating all of our business and official data and share it with different team departments so that they can analyse it and create a detailed analytics of past performances and also make required changes on it for future growth. **What do you dislike about Databricks?** One of the major challenge that we face while working with Databricks data intelligence platform is that you cannot use this tool with a single data scientist you will have to keep a team of professionals who can deal with large data and create multiple graphs and analytics according to available information and this complete activity involves lot of financial investment **What problems is Databricks solving and how is that benefiting you?** This software help us in making sure that all the data of different departments are accommodated in a same software so that access can be easier and decisions can be taken much quicker. With the help of this tool data of all the departments like finance, operations, sales and marketing are screend in one time and thoroughly interchecked too. **Official Response from Janelle Glover:** > It's fantastic to hear how Databricks Data Intelligence Platform is benefiting your business by streamlining access to data from different departments and facilitating quicker decision-making. We appreciate your feedback on the financial investment and will take it into consideration as we continue to improve user experience and ensure our platform is accessible for all users. ### 17. Powerful Warehousing, Collaborative, AI Debugging **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Banking | Small-Business (50 or fewer emp.) **Reviewed Date:** March 13, 2026 **What do you like best about Databricks?** As a growing Data Engineer, the community support and clear documentation of Databricks really helps me to guide through the problems. I've been managing the jobs and pipelines where failures are bound to happen, debugging with the Diagnose this error with AI feature has helped me with fasterthe failure recovery SLA. The UI is neat and makes it very easy to move between notebooks, SQL, and PySpark without much friction. Since I work with a team, collaboration is must. Sharing notebooks and iterating with teammates feels easy. I really like that I can rely on the ABAC policies to setup the Data Quality and Governance. **What do you dislike about Databricks?** I am not hundred percent sure if I would use the term dislike, I think it's just a personal preference. I sometimes feel the compute being used is a lot more than it should be for a simple query. Maybe the shuffle read/write that always gets involved when you're using a delta tables sometimes slows down the job. **What problems is Databricks solving and how is that benefiting you?** Databricks is helping our clients to manage the lakehouse and warehouse architecture in a much more structured way. We use it as the landing layer from S3 and then process data through our medallion architecture (bronze, silver, and gold) before delivering it to the final products. It’s been very effective for orchestrating daily jobs and pipelines. I also really like the asset bundles and how easily everything integrates with Git, which makes version control and deployments much smoother for the team. I am more likely to use Databricks as my go to platform for data lakehouse and warehousing. **Official Response from Janelle Glover:** > Thank you for sharing your positive experience with Databricks. We're thrilled to hear that our community support, documentation, and collaboration tools are helping you and your team manage daily jobs and pipelines effectively. We understand your concern about compute usage and shuffle read/write, and we will take your feedback into account as we continue to enhance our platform. We appreciate your support and look forward to continuing to serve your data engineering needs. ### 18. Finally Databricks Data Intelligence Platform has given us stability with Spark jobs. **Rating:** 5.0/5.0 stars **Reviewed by:** Preetham C. | Senior Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** January 06, 2026 **What do you like best about Databricks?** I am glad my leg is not completely dead from having to wait for a query (at least the auto termination feature works and saved me money) History is somewhat useful I rely on it to pull up previous scripts I write because I always seem to forget what I did the day before. I think it helps keep finance off my back by saving them money on the AWS bill. To me, it's simply one central location for managing our big data so I do not have to watch 5 monitors. **What do you dislike about Databricks?** If I want to find a query that was run over 30 days ago the search function does not even come close to being able to help me and also installing R Packages is a complete nightmare and the error messages are as clear as mud. And when working with large amounts of data the user interface becomes sluggish and trying to scroll through a notebook is like pushing through the mud. It would be nice if it were easier to install/ manage external spark packages. **What problems is Databricks solving and how is that benefiting you?** We create Machine Learning Models and perform Heavy ETL for the Analytics Department. It does a good job partitioning our data so we can query smaller time frames without having to sit around for hours waiting. It also allows our data team to focus on their actual work rather than constantly fixing broken clusters which is nice. **Official Response from Janelle Glover:** > Thank you for taking the time to share your feedback! We're glad to hear that our platform has provided stability for your Spark jobs and that the auto-termination feature has been beneficial in saving costs. We appreciate your notes on the history feature and the centralization of big data management and will take these concerns into consideration. ### 19. Unified Platform that Enhances Data Team Collaboration **Rating:** 5.0/5.0 stars **Reviewed by:** Andrew W. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** June 17, 2026 **What do you like best about Databricks?** I like that Databricks makes it easy to build processes on top of a data warehouse in a single unified platform. It really helps in making it easy for data engineers and data scientists to work together without needing to move data between systems. **What do you dislike about Databricks?** Right now it’s clunky to manage Azure Active Directory groups and syncing with Databricks. I think there is a solution coming. **What problems is Databricks solving and how is that benefiting you?** I use Databricks to deliver apps and machine learning models, solving sales promotions effectiveness and labor and product demand issues. It makes it easy for data engineers and data scientists to collaborate without moving data between systems, all in a single platform. **Official Response from Aunalisa Arellano:** > It's great to hear that Databricks is helping you deliver apps and machine learning models to solve business challenges. We appreciate your feedback and are committed to providing a seamless collaboration experience for data teams. ### 20. Streamlined Data Management with Databricks **Rating:** 5.0/5.0 stars **Reviewed by:** ROHITH S. | Mid-Market (51-1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I like the Genie features in Databricks, which allow users to query their requests using natural language. The data processing speed is impressive, often taking just minutes to hours. Our data pipeline's robust processing eliminates manual pipeline tuning, ensuring fresh governed data is available for business consumption. **What do you dislike about Databricks?** Automated governance boundaries could be improved. The initial configuration and platform setup was time-consuming. **What problems is Databricks solving and how is that benefiting you?** I use Databricks to improve data quality, standardize data, and generate business insights. The Genie feature allows querying requests using natural language, making data processing much quicker and more efficient. The robust data pipeline eliminates manual tuning and ensures fresh data is ready for business use. **Official Response from Janelle Glover:** > We're glad to hear that you are enjoying Genie and the data processing speed in Databricks. We appreciate your feedback on the automated governance boundaries and initial setup, and we will take this into consideration for future improvements. ### 21. All-in-One Platform with Collaborative Notebooks and Fast, Scalable Processing **Rating:** 4.5/5.0 stars **Reviewed by:** Vikash M. | Chief Marketing Manager, Small-Business (50 or fewer emp.) **Reviewed Date:** May 30, 2026 **What do you like best about Databricks?** What I like most about Databricks is how it brings data engineering, analytics, and AI into one platform. The collaborative notebooks, fast processing, and easy scalability save a lot of time, especially when working with large datasets and multiple teams on shared projects. **What do you dislike about Databricks?** Databricks can become expensive quickly, and cluster management still feels confusing for beginners sometimes. **What problems is Databricks solving and how is that benefiting you?** Databricks simplifies large-scale data processing, analytics, and AI workflows, helping me save time, collaborate better, and manage massive datasets more efficiently. **Official Response from Jess Darnell:** > It's great to hear that Databricks is helping you simplify large-scale data processing, analytics, and AI workflows. We're committed to providing a platform that saves time, fosters collaboration, and improves efficiency in managing massive datasets. ### 22. Versatile Platform with Robust Data Engineering, BI, and AI Capabilities **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User | Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I like that Databricks provides a cloud data lakehouse where I can do both AI and BI, and it allows for federated data using Unity Catalog. The data engineering, Genie Spaces, and data pipelines are all critical to my work. They help us build and deploy a global data lake that pulls data from multiple ERPs and other sources, providing sales, supply chain, and finance insights quickly and easily. **What do you dislike about Databricks?** Clarity around cost. Everything is based on DBUs, which sometimes can be a little unclear what DBUs translate to in clear dollars. But they do provide good dashboards to see actual consumption in dollars. **What problems is Databricks solving and how is that benefiting you?** It provides a cloud data lakehouse where I can do both AI and BI, and have federated data using Unity Catalog. It allows building and deploying a global data lake, pulling data from multiple sources, and providing insights quickly and easily. **Official Response from Janelle Glover:** > We're pleased to hear that Databricks is helping you solve data engineering and analytics challenges, and we appreciate your insights on the benefits that Genie Spaces and Unity Catalog are bringing to your work. ### 23. Scalable and User-Friendly with Impressive Data Processing Speeds **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Manufacturing | Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I really like how Databricks has recently opened up all the apps for building dashboards, and the Ginie feature is pretty cool for providing insights over data. It's scalable and easy to use, which saves us time compared to our traditional ways of handling data. The speed at which it scans data is impressive, and building apps is super fast and cool, reducing development time efficiently. **What do you dislike about Databricks?** I believe the interoperability in terms of iceberg where Databricks, Delta tables are very easily known can be used within Snowflake as an iceberg table. Whereas the iceberg table from Snowflake to Databricks is not working yet for us. So that’s the area I feel like Databricks could have done something better or sooner for us. **What problems is Databricks solving and how is that benefiting you?** Databricks mainly solves a lot of data engineering problems, processing large volumes of logs efficiently in our database engineering system. **Official Response from Jess Darnell:** > Thank you for sharing your positive experience with Databricks, including the ease of building dashboards, the Genie features, and the impressive data processing speeds. We understand your concerns about the interoperability with Snowflake and the iceberg tables, and we will take that into account for future enhancements. ### 24. Efficient Yet Complex for New Users **Rating:** 5.0/5.0 stars **Reviewed by:** INBOXME 2. | Mid-Market (51-1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I like all the cool feature apps and Lakebase in Databricks, which make it less time-consuming to build. The 'stand table with UC' and syncing tables with UC and Lakebase enhance the experience, making things smoother. The setup with Azure was pretty straightforward with networking, and overall, it felt smooth and easy to use. **What do you dislike about Databricks?** More complicated for a new user. When starting out, it was challenging to understand clusters, what they are, and how they start. **What problems is Databricks solving and how is that benefiting you?** I use Databricks for data engineering, facilitating data transmission to get business insights. It offers cool feature apps and lakebase, which reduce build time, making it more efficient. **Official Response from Jess Darnell:** > We're glad to hear that you are enjoying the cool feature apps and Lakebase in Databricks, as well as the smooth setup with Azure. We understand that the platform may seem complex for new users, and we are continuously working to improve our onboarding process and provide more resources for beginners. ### 25. Complete Integration and Easy Configuration with Databricks **Rating:** 4.5/5.0 stars **Reviewed by:** Pedro H. | Small-Business (50 or fewer emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I like how the components of Databricks are integrated into a single platform, covering everything from a simple ETL to job orchestration. This integration makes it much easier because the client doesn't need numerous employees working on various components, especially in the IT area. This really simplifies implementation and allows for more focus on the business area. **What do you dislike about Databricks?** I would say a policy that is a bit more accessible and more transparent associated with the costs. **What problems is Databricks solving and how is that benefiting you?** Databricks solves business problems and integrates components into a single platform, facilitating implementation by focusing on the business area without the need for many employees for different IT tasks. **Official Response from Janelle Glover:** > We're glad to hear that you find Databricks’ integrated platform beneficial for your business needs. We appreciate your feedback about cost transparency and accessibility, and we'll consider it for future improvements. ### 26. Seamless Web-Based Analytics with Some Learning Curve **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User | Small-Business (50 or fewer emp.) **Reviewed Date:** July 08, 2026 **What do you like best about Databricks?** I really like that Databricks is integrated in a web browser, which makes it extremely easy to access. Anyone with access to a web browser and authentication to our data system can do self-service analytics. This is a big improvement from when we used Teradata, which was extremely slow and required downloading an application. Now, with Databricks, everything's in the web browser and that's a major plus. **What do you dislike about Databricks?** I believe that Databricks can be improved by maybe having a more useful path for beginners. Sometimes it could be a steep learning curve when learning Databricks, understanding what queries do, understanding what's the difference between notebooks, jobs, workspaces, etc. **What problems is Databricks solving and how is that benefiting you?** Databricks solves our problems by providing everything needed for data transformation, processing, analytics, SQL queries, and machine learning models, all in one place. **Official Response from Jess Darnell:** > We're glad to hear that you find Databricks easy to access and that it has improved your analytics process. We appreciate your feedback on the learning curve and will take it into consideration for future improvements. ### 27. Fast and Intuitive, Perfect for Unified Data Management **Rating:** 5.0/5.0 stars **Reviewed by:** David C. | Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I use Databricks for data warehouse and analytics dashboard tasks. I really appreciate how it brings my data into one place, which is super helpful for managing everything efficiently. I like its speed and user interface, which are standout features for me. Additionally, I can use various languages on one notebook, making it really versatile and useful for different programming needs. The initial setup was fairly easy, which was a nice surprise. **What do you dislike about Databricks?** Easier to understand. Maybe add more tutorials. **What problems is Databricks solving and how is that benefiting you?** Databricks brings my data into one place and allows me to use various languages on one notebook, enhancing my data warehouse and analytics experience. **Official Response from Janelle Glover:** > We're thrilled to hear that Databricks has been a valuable tool for your data management and analytics tasks. We appreciate your feedback on the platform's speed, user interface, and versatility. We'll definitely take your suggestion for more tutorials into consideration to enhance the user experience. ### 28. Practical and Efficient for Improving Financial Processes **Rating:** 5.0/5.0 stars **Reviewed by:** Clifford J. | Technical Support, Small-Business (50 or fewer emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I like that Databricks is very practical and that it has a lot of documentation at hand along with genie code. This helps us improve report delivery times and have information readily available. I also value how Databricks allows less technical users to build ideas that previously only more technical people could develop. Additionally, the initial setup was super easy, which reinforces its practicality. I recommend it whenever I can. **What do you dislike about Databricks?** With the new, improve **What problems is Databricks solving and how is that benefiting you?** Databricks improves report delivery times, provides us with easy access to information, and helps non-technical users develop ideas. **Official Response from Aunalisa Arellano:** > We're glad to hear that you find Databricks practical and efficient for improving financial processes. Our documentation and Genie Code are designed to make report delivery times faster and information readily available. We appreciate your recommendation and look forward to continuing to support your needs. Thank you for taking the time to leave a review and choosing Databricks! ### 29. Lakebase is great but needs better monitoring & auditing **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Health, Wellness and Fitness | Enterprise (> 1000 emp.) **Reviewed Date:** March 24, 2026 **What do you like best about Databricks?** Bidirectional Sync capabilities in Databricks Lakebase & Lakehouse allows us to establish continuous healthcare intelligence where analytics in Lakehouse and operations in OLTP Lakebase remain tightly connected. We invested heavily in the modern Lakehouse architectures for enterprise data analytics AI and discovery. Clinical systems and patient interaction data flow into governed Databricks Lake houses where we build Care 360 views and healthcare key insights. **What do you dislike about Databricks?** Setting up Sync process requires extensive curation and planning to achieve great outcomes. Cost management is a big concern when multiple teams as multiple departments in my org have various policies. The records are dropped if the PK is null for data in lake houses. There's room for improvement to better handle it in future **What problems is Databricks solving and how is that benefiting you?** Databricks solves ingestion, transformation, governance, and data quality challenges, offering AI and BI tools for instant insights. Bidirectional Data sync (Lakehouse -> Lakebase) processes can operate together as a unified architectural pattern in the Enterprise Healthcare Intelligence Platform. Healthcare enterprises have historically struggled because analytical systems and operational systems evolved independently. Bidirectional Sync introduces a unified model where Analytics, Operational serving, AI activation & Continuous learning coexist within the same governed ecosystem that significantly reduces Data duplication, Pipeline sprawl & Synchronization complexity while improving Operational intelligence, Data freshness, Auditability & Decision latency. Forward Sync operationalizes healthcare intelligence. Reverse Sync reactivates operational knowledge back into the learning system. Together, they establish a continuous intelligence architecture where every healthcare interaction contributes toward improving patient outcomes, operational efficiency and AI effectiveness at enterprise scale. **Official Response from Janelle Glover:** > Thank you for sharing your positive experience with Genie and Databricks. We appreciate your feedback on setting up Genie. We are continuously working to enhance our semantic model and cost management features for a better user experience. ### 30. Boosts Productivity with Easy Setup, Needs Better Semantic Model **Rating:** 5.0/5.0 stars **Reviewed by:** Frederik S. | Senior Machine Learning Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I really like the Genie feature in Databricks as it enhances my productivity significantly—I'd say it boosts it by 10x. It helps me write code more efficiently, manage workflows better, and apply best practices effectively. The initial setup was also very easy, which was a big plus. **What do you dislike about Databricks?** The semantic model layer in Databricks could be improved. Power BI has more time intelligence, which is hard to replicate in Databricks metric views. Migration is also hard. **What problems is Databricks solving and how is that benefiting you?** I use Databricks for ingestion, storage, transformation, orchestration, and data exposure with governance. It boosts my productivity, especially in writing code, managing workflows, and applying best practices. **Official Response from Jess Darnell:** > We're glad to hear that you find Databricks' Genie feature to be a significant productivity booster and that the initial setup was easy for you. We appreciate your feedback on the semantic model layer and will take it into consideration for future improvements. ### 31. Databricks Data Intelligence Platform actually works and saves money **Rating:** 5.0/5.0 stars **Reviewed by:** Christopher C. | Sales Operations Manager, Small-Business (50 or fewer emp.) **Reviewed Date:** December 21, 2025 **What do you like best about Databricks?** The autoscale works well; it also helped us reduce the cost of using cloud resources. I thought that was going to be a problem since this is the first time we used autoscale. The support has been good enough, they normally appear on time for their scheduled hours to assist us in fixing the problems we create. The ability to save the query history in order of how the queries were written is nice as I often forget what I write a few minutes after writing it. When working with coworkers who need access to your code you can send them the permalink (link) to the code which is better than having to explain it. Since it supports both Spark and Presto within one tool I do not have to jump between tools. **What do you dislike about Databricks?** I hate the way the search function works. I have never found the results from a month ago, and it is annoying. The UI will occasionally lag behind my typing, and if I am in a rush I feel it takes too long. Also it would make much more sense for the tables drawer to remain open when I click on the notebook and instead of closing automatically which is very time consuming as I need to reopen it again. I have had the support team tell me they cannot replicate an issue which is no help at all. **What problems is Databricks solving and how is that benefiting you?** We are able to process large amounts of data using Databricks without having to build out a large ops team to manage our clusters. We can scale up and down so we only pay for the time we are running jobs in the cloud. I use it to see sales numbers on a daily basis although I am not a data engineer. Databricks allows us to run pipelines with Airflow without all of the things crashing right away. Databricks reduces the amount of admin work involved in building and managing clusters. **Official Response from Janelle Glover:** > Thank you for sharing your positive experience with Databricks Data Intelligence Platform! We're pleased to hear that the platform has helped you save costs and streamline your data processing. We understand your concerns about the search function and UI, and we'll work on addressing these issues to enhance your user experience. We appreciate your feedback! ### 32. Databricks Makes Collaboration and Reliable Data Pipelines Easy **Rating:** 4.0/5.0 stars **Reviewed by:** Raja B. | Senior Solutions Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** March 28, 2026 **What do you like best about Databricks?** I really enjoy working in the Databricks environment because it makes it easy to collaborate with others through shared notebooks. Delta Lake technology has also been great for ensuring data quality and reliability across our pipelines. It lets us manage data, build pipelines, and run AI/BI workloads all in one place. **What do you dislike about Databricks?** The interface is quite laggy at times, especially when I’m scrolling through a notebook or spinning up a cluster. **What problems is Databricks solving and how is that benefiting you?** Because it’s a unified, end-to-end platform covering everything from data ingestion and transformation to AI and BI insights, it enables faster analysis and helps convert complex datasets into actionable decisions more efficiently **Official Response from Janelle Glover:** > We're thrilled that Databricks has been beneficial for your data pipelines and analysis. We're sorry to hear that you have experienced lags in the interface. We appreciate your feedback on this, and our team will work to address this. ### 33. Flexible Data Integration for Reporting and AI **Rating:** 4.5/5.0 stars **Reviewed by:** Balajee S. | SAP BW-BO /SAP HANA Architect - Onshore (Stellium Inc.,), Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I like the flexibility to source data from multiple transactional (structured) systems as well as IoT (unstructured) systems, and to integrate everything seamlessly. From there, I can build a solid data foundation on top of that data, which can then be used for both reporting and AI. **What do you dislike about Databricks?** It would be helpful to have more user-friendly UI options for non-IT folks who want to try their hand at data modeling and reporting. **What problems is Databricks solving and how is that benefiting you?** It handles big data efficiently and lets me run ML models on a huge historical dataset spanning 20+ years, even when that data is spread across multiple multi-million-record tables. **Official Response from Aunalisa Arellano:** > Thank you for sharing your positive experience with Databricks! We're thrilled to hear that you appreciate the flexibility and seamless integration for your data needs. We understand your feedback about the user-friendly UI for non-IT users and will certainly take that into consideration for future improvements. Our goal is to make data modeling and reporting accessible to all users, and we appreciate your input on how we can enhance the experience. If you have any specific suggestions or further feedback, please feel free to reach out. We're here to support you in maximizing the benefits of Databricks for your reporting and AI needs. ### 34. Enhanced Data Management with Some Connectivity Challenges **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User | Mid-Market (51-1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I really love using Databricks, especially for the Unity Catalog. Genie is a real help when it comes to database tasks and connecting to APIs or writing code, correcting mistakes and solving issues. The AI aspect of it is fun and quite beneficial to my workflow. **What do you dislike about Databricks?** The major improvement that I look forward to in Databricks is how all these, whether it's data lakehouse, Genie two, all these areas, how it will connect. Providing more guidance with respect to training is where I'm looking forward to that kind of improvement. One of the major difficulties is while connecting to serverless, we find it's losing the connectivity. **What problems is Databricks solving and how is that benefiting you?** Databricks solves the major challenge of understanding complex data by providing layers to analyze it well and aids in connecting to APIs or writing code with fewer mistakes, thanks to Genie. **Official Response from Janelle Glover:** > Thank you for sharing your positive experience with Databricks, particularly the benefits of using Genie. We acknowledge the connectivity challenges you've faced and are committed to enhancing the platform's connectivity, including providing more guidance for training. Your feedback is valuable to us. ### 35. Seamless AI Deployment and Management Powerhouse **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User | Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I love that Databricks lets me use the latest and greatest in open source and allows me to use distributed computing across the compute layer. It helps me serve AI to scale and monitor compute through a unified API where I can track costs and permissions. Managing a lot of users is easy, with the capability to use groups, permissions, and catalogs to make everything straightforward. It allows me to handle everything in an easy way and manage all of our permissions and governance in one platform. **What do you dislike about Databricks?** The rapidly evolving ecosystem makes it hard to build things that are durable. They have constantly changing SDKs and APIs, and versioning. **What problems is Databricks solving and how is that benefiting you?** I use Databricks to build AI agents for students, manage distributed computing, track costs and permissions, serve AI to scale, and handle users easily with groups and permissions. **Official Response from Aunalisa Arellano:** > We're glad to hear that you are enjoying the capabilities of Databricks, especially its support for open source technologies and distributed computing. We understand that managing a rapidly evolving ecosystem can be challenging, and we are continuously working to improve our SDKs and APIs to provide a more stable experience for our users. Thank you for taking the time to leave a review! It means so much to us. ### 36. Unified, User-Friendly Platform That Accelerates Data Insights **Rating:** 4.5/5.0 stars **Reviewed by:** ANIKET S. | Student, Mid-Market (51-1000 emp.) **Reviewed Date:** December 19, 2025 **What do you like best about Databricks?** What I like best about the Databricks Data Intelligence Platform is how it brings everything data engineering, analytics, and machine learning together in one unified environment. It’s very user-friendly despite being powerful, and it makes collaboration between technical and non-technical teams much easier. The platform handles large volumes of data efficiently, scales smoothly, and integrates well with cloud services, which saves a lot of time and effort. Overall, it helps turn raw data into meaningful insights faster without making the process overly complex. **What do you dislike about Databricks?** One thing I dislike about the Databricks Data Intelligence Platform is that it can feel complex and overwhelming for new users, especially those without a strong technical background. The learning curve is quite steep, and it takes time to fully understand how to use all the features effectively. Additionally, the pricing can become expensive as usage scales, and cost management isn’t always very transparent. Sometimes, debugging errors or performance issues can also be challenging, particularly in large or highly integrated workflows. **What problems is Databricks solving and how is that benefiting you?** Databricks Data Intelligence Platform solves the problem of working with fragmented data systems by bringing data engineering, analytics, and machine learning into a single, unified platform. Instead of managing multiple tools, everything is available in one place, which reduces complexity and data silos. This benefits me by saving time, improving collaboration across teams, and enabling faster access to reliable insights. It also handles large-scale data processing efficiently, allowing better decision-making based on real-time and accurate data rather than delayed or incomplete information. **Official Response from Janelle Glover:** > Thank you for highlighting the benefits of the Databricks Data Intelligence Platform in solving the challenges of fragmented data systems. We are committed to providing a unified platform that saves time, improves collaboration, and enables faster access to reliable insights. We also appreciate your feedback about the learning curve and pricing concerns. We are constantly working to improve user experience and transparency, and your input is valuable in that process. ### 37. Superb Centralization, Minor Cost Clarity Issues **Rating:** 5.0/5.0 stars **Reviewed by:** Nelson Eduardo C. | Mid-Market (51-1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I really like Databricks because it centralizes everything, allowing me to control all aspects related to data on one platform. It's also easier to use compared to other tools and gives me better control over costs. The initial setup was really easy, which is a big plus for me. **What do you dislike about Databricks?** I have a lot of dashboards, but we do not know what actions are required in order to lower cost. Cost clarity and how to reduce the cost could be improved. **What problems is Databricks solving and how is that benefiting you?** I use Databricks to understand customer behavior, product sales, and logistics. It centralizes everything, allowing control over data effortlessly. **Official Response from Jess Darnell:** > Thank you for sharing your positive experience with Databricks and highlighting the ease of setup and centralized data control. We understand the importance of cost clarity and will strive to enhance this aspect for our users. ### 38. Effortless Data Analytics and App Building **Rating:** 4.0/5.0 stars **Reviewed by:** Moksha D. | Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I use Databricks for data analytics, building agents and apps. It makes analytics easy and quick, and helps maintain data and control versions easily. I really enjoy the app and agent building capabilities, as building apps used to require much effort, but now it’s easier with Databricks. Additionally, the initial setup was smooth. **What do you dislike about Databricks?** Agent handling things could be improved. We create agents through UI, which makes it easy to create but doesn’t give you full control on handling it. **What problems is Databricks solving and how is that benefiting you?** I find Databricks makes analytics easy and quick, helps maintain data and control versions easily, and simplifies app building significantly. **Official Response from Jess Darnell:** > We're thrilled to hear that Databricks has simplified your data analytics and app building processes. We value your input on agent handling and will use it to enhance the user experience. Thank you for choosing Databricks. ### 39. Efficient Data Management with Intuitive Interface **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User | Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I use Databricks for querying my production data from S3 and for development and debugging using production data. I like how easy it is to navigate the platform and find what I need. I appreciate that Databricks allows me to run new code against production data in a safe way. I like the notebooks, which allow me to work adhoc. I also like the Unity Catalog for reviewing my data lake. It's easy to get started on. **What do you dislike about Databricks?** I feel like I don’t know enough about all of Databricks' utility, thus I only use a fraction of it. If it had prompts that could show me useful features, like tool tips. **What problems is Databricks solving and how is that benefiting you?** I use Databricks to query and develop with production data from S3. It lets me safely run new code against prod data, which isn't otherwise possible. **Official Response from Aunalisa Arellano:** > We appreciate your positive feedback about Databricks' intuitive interface and its benefits for querying and developing with production data. We understand the need for better guidance on utilizing the full range of Databricks' features, and we're committed to improving the platform to provide more helpful prompts and tooltips for users. We also encourage you to check out the Databricks Academy if you haven't yet. It is an excellent resource to learn all about the product. ### 40. Centralizes Tools Efficiently, Needs Fast Serverless **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User | Mid-Market (51-1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I like how every tool in Databricks is centralized, which means I don't need to open up many software or sites. It enhances my efficiency, especially when I'm using Genie to debug an issue more quickly so I can deliver the task at hand. **What do you dislike about Databricks?** Genie is constantly improving but having serverless startup times be quicker and or not crash. When using serverless compute in Unity Catalog, times where the serverless compute will crash. It worries me because I don't wanna rack up costs. However, I don't think it is doing that on the back end, but it is the first instinct. **What problems is Databricks solving and how is that benefiting you?** I use Databricks to turn large data forms into bite-sized pieces and filter down anomalies. It helps me visualize and create dashboards in a centralized place, enhancing efficiency, especially when using Genie for quick debugging. **Official Response from Jess Darnell:** > We're thrilled to hear that you appreciate the centralized tools and Genie's efficiency in Databricks. We understand your concerns about serverless compute startup times and crashes. Our team is actively working on improving the performance and stability of serverless compute to ensure a seamless experience for our users. Thank you for your valuable feedback, and we're committed to addressing these issues. ### 41. Unified Governance and AI Solutions with Databricks **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User | Mid-Market (51-1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I set up Databricks environments for clients as a data engineer, and it helps me build complete enterprise data and AI solutions on a single platform. I particularly like the Databricks governance and AI platform capabilities both for myself and my clients. Databricks provides the tools to manage everything on the same platform where the data is housed, which simplifies governance. The ability to manage groups of users' access to both data and AI resources from a single location simplifies governance a lot. **What do you dislike about Databricks?** The barrier to entry and ability to create solid production pipelines can be higher than other platforms or standalone tools. **What problems is Databricks solving and how is that benefiting you?** Databricks helps me build complete enterprise data and AI solutions for clients on a single platform. Its governance and AI capabilities allow managing access to data and AI resources easily, simplifying complex operations. **Official Response from Aunalisa Arellano:** > Thank you for sharing your positive experience with Databricks! We're thrilled to hear that our platform has been instrumental in helping you build enterprise data and AI solutions efficiently. We appreciate your feedback on the barrier to entry and production pipeline creation, and we are continuously working to improve user experience and streamline processes. If you have any specific suggestions or encounter any challenges, please feel free to reach out to our support team. We value your partnership and look forward to continuing to support your data engineering needs. ### 42. Streamlined Data Management and Transformation **Rating:** 4.0/5.0 stars **Reviewed by:** Puttaraju D. | Associate, Mid-Market (51-1000 emp.) **Reviewed Date:** May 14, 2026 **What do you like best about Databricks?** I use Databricks for storing and consuming data. I really like the unified catalog feature, as it helps me manage permissions and access to metadata easily. The ability to publish datamart data to Thoughtspot is beneficial, and I find data transformation using Databricks notebooks particularly helpful. The ease of initial setup with Databricks was great and our team of over 1000 people transitioned smoothly from Hadoop. **What do you dislike about Databricks?** Table level access. Provision to restrict access at table level is required. **What problems is Databricks solving and how is that benefiting you?** I use Databricks for storing and consuming data, with a unified catalog for easy access to metadata. The ability to transform and publish datamart data to Thoughtspot is valuable, though I'd like improved table-level access restrictions. **Official Response from Jess Darnell:** > Thank you for sharing your positive experience with Databricks, especially regarding the unified catalog feature and the ease of initial setup. We understand your concern about table-level access and will take that into account for future enhancements. ### 43. Effortless Large-Scale Data Ingestion with Databricks **Rating:** 5.0/5.0 stars **Reviewed by:** Sairam K. | Analyst II , Engineering support, Internet, Mid-Market (51-1000 emp.) **Reviewed Date:** October 24, 2019 **What do you like best about Databricks?** I love the future features of Databricks from the summit, including using agents, genie, bricks, the unification of catalog formats, lakebase, and lakehouse. It's an easy way to be portable without worrying about the underlying data format. I especially appreciate that it allows ingesting data at scale automatically with agents who understand the context of the workload. Additionally, the initial setup of Databricks was very easy for me. **What do you dislike about Databricks?** Documentation could be improved. **What problems is Databricks solving and how is that benefiting you?** I use Databricks for ingesting data at scale with low latency, and it's an easy way to be portable without worrying about underlying data formats. **Official Response from Aunalisa Arellano:** > We're glad to hear that you appreciate the good UI, integrations, speed, and efficiency of our platform. We're also pleased that you find our updates beneficial. Thanks for taking the time to leave a review! ### 44. Promising Potential in Data Latency Reduction **Rating:** 4.5/5.0 stars **Reviewed by:** Gustavo C. | Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I like the ease and availability of the solutions that Databricks offers. The tool simplifies the use of various different tools at various stages of the process, reducing the operational cost which can be quite expensive and facilitating the training of people. This unique platform meets various requirements, which gives me the freedom to then deal with the problems. **What do you dislike about Databricks?** I can't give an opinion yet **What problems is Databricks solving and how is that benefiting you?** I use Databricks to reduce latency in large volumes of data and ensure access to regulatory protected data. It simplifies processes, reduces operational costs, and facilitates empowerment with a single platform. **Official Response from Aunalisa Arellano:** > It's great to hear that Databricks is helping you reduce data latency and ensure access to regulatory protected data. We're dedicated to providing a platform that simplifies processes and reduces operational costs. Thank you for choosing Databricks. ### 45. Powerful unified data platform with great collaboration **Rating:** 4.5/5.0 stars **Reviewed by:** Varun G. | Project Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** December 13, 2025 **What do you like best about Databricks?** Databricks is easy to use and simple to get started with, even when handling large amounts of data. It brings everything like data processing, analytics, and AI into one place, so my team do not need multiple tools. The platform integrates smoothly with common tools like BI dashboards, workflows, and cloud services. Its notebooks make day to day work frequent and convenient by allowing our teams to collaborate in real time. There are many built in features for data, analytics, and machine learning without added complexity. Customer support, documentation, and community resources make it easier to solve issues quickly. **What do you dislike about Databricks?** Databricks can be expensive and unpredictable in cost, especially for small teams if workloads run longer than expected. It takes technical expertise to set up, manage, and optimize performance, which can be challenging for non-technical users. Costs need frequent monitoring since compute and storage are billed separately. While it has basic dashboards, it still depends on tools like Power BI or Tableau for full reporting. **What problems is Databricks solving and how is that benefiting you?** Databricks solves the problem of managing data across many different tools by putting everything in one place. This saves time, reduces confusion, and makes it easier for teams to work together. It helps us handle large data smoothly, keep access and security under control, and get useful insights faster even for people who are not very technical. **Official Response from Janelle Glover:** > Thank you for highlighting the benefits of using Databricks for managing data and improving collaboration within your team. We understand the importance of cost predictability and ease of use, and we're actively working to enhance these aspects of our platform. ### 46. Unified Data Platform That Simplifies Complex Workflows **Rating:** 4.0/5.0 stars **Reviewed by:** PRATYUSH A. | Student and researcher, Small-Business (50 or fewer emp.) **Reviewed Date:** December 13, 2025 **What do you like best about Databricks?** What I like best about Databricks is how it brings data engineering, analytics, and machine learning together on one platform. Having a unified environment built around Apache Spark makes collaboration between data teams much easier. The Lakehouse approach works well because it removes the need to move data across multiple tools. Performance is strong for large datasets, and notebooks make experimentation, analysis, and collaboration more efficient. Overall, it simplifies complex data workflows while still being powerful. **What do you dislike about Databricks?** The main downside is the cost and complexity for new users. Pricing can be hard to predict, especially when workloads scale unexpectedly, and compute costs can rise quickly if not monitored closely. There is also a learning curve for teams that are not already familiar with Spark or cloud-based data platforms. Some advanced configurations and optimizations require experienced resources, which can slow adoption for smaller or less mature data teams. **What problems is Databricks solving and how is that benefiting you?** Databricks helps us solve the problem of working with large, fragmented datasets across different tools and teams. Earlier, data engineering, analytics, and machine learning were handled in separate systems, which created silos and slowed down insights. With Databricks, we can process, analyze, and model data on a single platform, which improves collaboration and reduces data movement. From a business perspective, it helps us generate insights faster, scale analytics as data grows, and improve data reliability. This leads to quicker decision-making, more consistent reporting, and better use of data for forecasting and optimization, while reducing operational overhead. **Official Response from Janelle Glover:** > It's great to hear that Databricks has helped streamline your data workflows and improve collaboration across teams. We recognize the challenges around cost, complexity, and the learning curve, and we are dedicated to addressing these concerns to ensure a more seamless experience for all users. Thank you for your valuable feedback. ### 47. Centralization and Flexibility in Data Management **Rating:** 5.0/5.0 stars **Reviewed by:** Hector B. | Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Databricks?** I like that Databricks is completely centralized, has a good governance system, and is super flexible. Additionally, I value its ease and speed in handling large amounts of data, which is vital for my data engineering team. I also highlight that the initial setup was super easy. **What do you dislike about Databricks?** They could improve the use of reports to have visibility of cost, how much a query costs me. **What problems is Databricks solving and how is that benefiting you?** I use Databricks for the agile management of large amounts of data, creation of jobs and reports. Its centralization and good governance provide critical visibility for my data engineering team. **Official Response from Jess Darnell:** > We're glad to hear that you find Databricks centralized, flexible, and easy to set up. We appreciate your feedback about the need for improved cost visibility in reports and will take this into consideration for future enhancements. ### 48. Efficient Data Processing with Integrated AI **Rating:** 5.0/5.0 stars **Reviewed by:** Jason Y. | Mid-Market (51-1000 emp.) **Reviewed Date:** May 14, 2026 **What do you like best about Databricks?** I like that Databricks allows me to process lots and lots of data efficiently using SQL. I appreciate having data and AI in a single platform, and it's great that it improves by itself without needing additional licenses. It's really helpful that I don't need to manage the infrastructure or invest in tuning the platform because Databricks takes care of it for me. **What do you dislike about Databricks?** With the number of offerings increasing, it has become hard to find where things are located in the UI. **What problems is Databricks solving and how is that benefiting you?** I use Databricks for processing lots of data efficiently with SQL. It combines data and AI on one platform and auto-improves, so I don't manage infrastructure or invest in tuning. **Official Response from Jess Darnell:** > Thank you for sharing your positive experience with Databricks. We're pleased that you find the platform helpful in processing data efficiently and that it eliminates the need for managing infrastructure and tuning. We understand the challenge of navigating the UI with the increasing number of offerings and are working to enhance the user interface. ### 49. Simplifies Data Analysis for Streamlined Workflows **Rating:** 4.0/5.0 stars **Reviewed by:** Pragati V. | Social Media Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** January 06, 2026 **What do you like best about Databricks?** Databricks is a Data Analytics tool that is used by our designing engineers to analyse all the different type of financial and operational data of our company and create a summary of everything so that understanding of companies workflow can be simple. **What do you dislike about Databricks?** One of the major disadvantage of databricks is that the software is completely based on programming language like Python, SQL, Scala so if the user does not have knowledge of these programming languages than it is very difficult for them to use this platform. **What problems is Databricks solving and how is that benefiting you?** The best part of databricks is that it can easily get integrated with cloud networks like as azure, AWS, Google Cloud etc. So, working on this platform also help us in getting access to all the data of different years and compile them to get a proper analytics of business performance. **Official Response from Janelle Glover:** > It's great to hear that Databricks has helped you integrate with cloud networks and access historical data for business analytics. We understand that the programming language requirement may be a challenge for some users, and we appreciate you sharing your concerns with this. ### 50. End-to-End Data Lineage with Silver/Gold Layers for Powerful Analytics **Rating:** 5.0/5.0 stars **Reviewed by:** Venkatraman S. | Head of Data Analytics, Enterprise (> 1000 emp.) **Reviewed Date:** June 17, 2026 **What do you like best about Databricks?** It being a Datalake gives the ability track the lineage of the dat thru the entire lifecycle journey and also ability to provide the data at Silver layer for upstream and downstream applications to do what if analysis and also at same time be able to provided the agrregated dashboard in the gold layer **What do you dislike about Databricks?** People are still coming to terms with Medaalion structure and understanding it, and teh compute cost is also on higher side **What problems is Databricks solving and how is that benefiting you?** Well, it has been able to provide me the right enablement of data for my AI and ML ops **Official Response from Janelle Glover:** > It's great to hear that Databricks is enabling your AI and ML operations with the right data. We understand your concerns about the Medaalion structure and compute costs, and we are continuously working to improve and optimize these aspects. ## Databricks Discussions - [What is Lakehouse in Databricks?](https://www.g2.com/discussions/what-is-lakehouse-in-databricks) - 4 comments, 2 upvotes - [What are the features of Databricks?](https://www.g2.com/discussions/what-are-the-features-of-databricks) - 4 comments, 2 upvotes - [What does Databricks software do?](https://www.g2.com/discussions/what-does-databricks-software-do) - 3 comments - [What is Databricks unified analytics platform?](https://www.g2.com/discussions/what-is-databricks-unified-analytics-platform) - 3 comments - [View Databricks pricing details and edition comparison](https://www.g2.com/products/databricks/reviews?page=4&qs=pros-and-cons§ion=pricing&secure%5Bexpires_at%5D=2026-07-22+00%3A18%3A49+-0500&secure%5Bsession_id%5D=5872706f-4419-49c1-bad7-7dfce0713f01&secure%5Btoken%5D=da8ee1e4fd28fdaebdb7324f2d2d57e77923504900d11b7a75e507114141590a&format=llm_user) ## Databricks Integrations - 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Scalability **System** - Data Ingestion & Wrangling **Data Preparation** - Connectors - Data Governance **Data Management** - Data Integration - Data Compression - Data Quality - Built-In Data Analytics - In-Database Machine Learning - Data Lake Analytics **Management** - Data dictionary - Data Replication - Query Language - Data Modeling - Performance Analysis **Management** - Business Glossary - Data Discovery - Data Profililng - Reporting and Visualization - Data Lineage **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **Data Management** - Data Integration - Metadata - Self-service - Automated workflows **Scalability and Performance - Generative AI Infrastructure** - AI High Availability - AI Model Training Scalability - AI Inference Speed **Customization - AI Agent Builders** - Natural Language Configuration - Tone Customization - Security Guardrails **Agentic AI - DataOps Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Decision Making **Traffic Management & Performance - AI Gateways** - Token-Aware Rate Limiting - Semantic Caching - Multi-Model Routing & Fallbacks **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training **Database** - Real-Time Data Collection - Data Distribution - Data Lake **Data Transformation** - Real-Time Analytics - Data Querying **Compliance** - Sensitive Data Compliance - Training and Guidelines - Policy Enforcement - Compliance Monitoring **Functionality** - Extraction - Transformation - Loading - Automation - Scalability **Management** - Cataloging - Monitoring - Governing - Model Registry **Model Development** - Feature Engineering **Data Modeling and Blending** - Data Querying - Data Filtering - Data Blending **Integration** - AI/ ML Integration - BI Tool Integration - Data lake Integration **Maintenance** - Data Migration - Backup and Recovery - Multi-User Environment **Security** - Access Control - Roles Management - Compliance Management **Operations** - Metrics - Infrastructure management - Collaboration **Analytics** - Analytics capabilities - Dasboard visualizations **Cost and Efficiency - Generative AI Infrastructure** - AI Cost per API Call - AI Resource Allocation Flexibility - AI Energy Efficiency **Functionality - AI Agent Builders** - Omni-channel Support - Agent Branding - Proactive Response Capabilities - Seamless Human Escalation **Governance & Observability - AI Gateways** - Data Privacy - Cost Tracking - Centralized API Key Security **Machine/Deep Learning Services** - Computer Vision - Natural Language Processing - Natural Language Generation - Artificial Neural Networks **Integrations** - Hadoop Integration - Spark Integration **Data Quality** - Data Preparation - Data Distribution - Data Unification **Machine/Deep Learning Services** - Natural Language Understanding - Deep Learning **Deployment** - On-Premise - Cloud **Security** - Data Encryption - User Access Control **Maintainence** - Data Quality Management - Policy Management **Management** - Cataloging - Monitoring - Governing **Monitoring and Management** - Data Observability - Testing capabilities **Generative AI** - AI Text Generation - AI Text Summarization **Integration and Extensibility - Generative AI Infrastructure** - AI Multi-cloud Support - AI Data Pipeline Integration - AI API Support and Flexibility **Data and Analytics - AI Agent Builders** - Analytics & Reporting - Contextual Awareness - Data Privacy Compliance **Deployment** - Managed Service - Application - Scalability **Platform** - Machine Scaling - Data Preparation - Spark Integration **Connectivity** - Hadoop Integration - Spark Integration - Multi-Source Analysis - Data Lake **Performance ** - Scalability **Cloud Deployment** - Hybrid cloud support - Cloud migration capabilities **Generative AI** - AI Text Generation - AI Text Summarization **Generative AI** - AI Text Generation - AI Text Summarization **Security and Compliance - Generative AI Infrastructure** - AI GDPR and Regulatory Compliance - AI Role-based Access Control - AI Data Encryption **Integration - AI Agent Builders** - Workflow Automation - API Usage - Platform Interoperability - CRM Data Integration **Agentic AI - Analytics Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making **Self Service ** - Calculated Fields - Data Column Filtering - Data Discovery - Search - Collaboration / Workflow - Automodeling **Processing** - Cloud Processing - Workload Processing **Operations** - Data Visualization - Data Workflow - Governed Discovery - Embedded Analytics - Notebooks **Security** - Data Governance - Data Security **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image **Generative AI** - AI Text Generation - AI Text Summarization **Usability and Support - Generative AI Infrastructure** - AI Documentation Quality - AI Community Activity **Agentic AI - Data Governance** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Decision Making **Deployment & Integration - Analytics Platforms** - No-code Dashboard Builder - Report Scheduling and Automation - Embedded Analytics and White-labeling - Data Source Connectivity **Advanced Analytics** - Predictive Analytics - Data Visualization - Big Data Services **Generative AI** - AI Text Generation - AI Text Summarization **Agentic AI - Data Science and Machine Learning Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making **Performance & Scalability - Analytics Platforms** - Large data handling and Query Speed - Concurrent User Support **Advanced Analytics & Modeling - Analytics Platforms** - Data Modeling and Governance - Notebook and Script Integration - Built-in Predictive and Statistical Models **Agentic AI Capabilities - Analytics Platforms** - Auto-generated Insights and Narratives - Natural Language Queries - Proactive KPI Monitoring and Alerts - AI Agents for Analytical Follow-ups **Personalized Intelligence - Analytics Platforms** - Behavioral Learning for Contextual Query Refinement - Role-based Insight Personalization - Conversational and Prompt-based Analytics **Building Reports** - Data Transformation - Data Modeling - WYSIWYG Report Design - Integration APIs **Platform** - Mobile User Support - Customization - User, Role, and Access Management - Internationalization - Sandbox / Test Environments - Performance and Reliability - Breadth of Partner Applications ## Top Databricks Alternatives - [Cloudera](https://www.g2.com/products/cloudera/reviews) - 4.1/5.0 (131 reviews) - [Snowflake](https://www.g2.com/products/snowflake/reviews) - 4.5/5.0 (708 reviews) - [Teradata Autonomous Knowledge Platform](https://www.g2.com/products/teradata-autonomous-knowledge-platform/reviews) - 4.3/5.0 (356 reviews)