--- title: Databricks Reviews meta_title: 'Databricks Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 1365 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: 1365 scale: '5' date_modified: '2026-08-11' 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:** 1,365 ## About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics, and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, 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. 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. ### 2. 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! ### 3. Unified Platform Enhances Data Collaboration and Processing **Rating:** 4.0/5.0 stars **Reviewed by:** Monazah S. | DevOps Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** January 12, 2026 **What do you like best about Databricks?** I like the Databricks Data Intelligence Platform because it's a unified, scalable platform for data engineering, analytics, and collaboration. It simplifies the process of building and running data pipelines, handles performance-intensive Spark workloads, and promotes collaboration across teams with shared notebooks and environments. It's great for managing and processing large datasets, improving performance, and providing a consistent platform for turning raw data into insights. The initial setup was easy, thanks to helpful documentation. **What do you dislike about Databricks?** It can improve in areas like startup time for clusters, deeper visibility into performance tuning and clearer documentation for advanced configurations. **What problems is Databricks solving and how is that benefiting you?** I use the Databricks Data Intelligence Platform for large-scale data processing and analytics. It simplifies building reliable data pipelines, handles Spark workloads efficiently, reduces operational overhead, and enables team collaboration with shared notebooks. It's great for turning raw data into actionable insights. **Official Response from Janelle Glover:** > We're glad to hear that you find our platform unified, scalable, and easy to use for managing and processing large datasets. We appreciate your feedback and will take your suggestions for improvement into consideration. ### 4. It's super handy for analytics, scales well, and you can easily rely on it. **Rating:** 4.0/5.0 stars **Reviewed by:** Omar J. | Full Stack Web Developer, Small-Business (50 or fewer emp.) **Reviewed Date:** August 26, 2025 **What do you like best about Databricks?** The best thing about Databricks is that it very easily consolidates data engineering, data science, and analytics – all in one place Therefore, I can process huge data sets quickly, run very complex machine learning operations, all without switching tools. Collaboration through notebooks with my team in real-time really reduced a lot of back and forth that I used to have. **What do you dislike about Databricks?** The big issue is pricing can quickly ramp up if I’m not careful with cluster size or if I forget to turn them off. I had to learn how to use some of the more advanced features, like Unity Catalog and MLflow connectors if I was to use them well. The only thing I would add is an easy interface, like in some BI products. It may be overwhelming for the newbie. **What problems is Databricks solving and how is that benefiting you?** I can construct fraud detection models, run queries over billions of rows, and test proof-of-concepts for clients all on one platform. This cost me days in setting work up. Huge workloads on peak hours will not slow me down as I can scale my computing power instantly. This is why I think Databricks gives me more freedom to play around with data models and machine learning at scale as compared to Snowflake or any other alternative. **Official Response from Aunalisa Arellano:** > We're glad to hear that you find Databricks Data Intelligence Platform handy for analytics and that it consolidates data engineering, data science, and analytics in one place. We understand your concern about pricing and the learning curve for advanced features. We appreciate your feedback and will continue to work on improving the user experience and pricing. ### 5. Great platform for big data and ML, with some learning curve **Rating:** 4.5/5.0 stars **Reviewed by:** Amit K. | Build Connx, Small-Business (50 or fewer emp.) **Reviewed Date:** August 08, 2025 **What do you like best about Databricks?** What I really like about Databricks is how it brings everything—data engineering, analytics, and machine learning—into one place. It saves a lot of time when switching between workflows. The collaborative notebooks are super handy when working with a team, and the Spark integration just works without much hassle. Delta Lake is also a plus—being able to manage large datasets with versioning and ACID support is honestly a lifesaver in production scenarios. **What do you dislike about Databricks?** The platform can feel a bit intimidating at first, especially if you're new to big data tools. Setting up clusters and understanding the pricing model took me a while. Also, the UI sometimes lags when you're dealing with large notebooks or switching between multiple tabs. I wish the onboarding was a bit more beginner-friendly **What problems is Databricks solving and how is that benefiting you?** Databricks helps us streamline our entire data pipeline — from ingestion to analytics to machine learning. Earlier, managing large-scale datasets and running ML models used to be fragmented across tools, but Databricks made it way smoother. It saves us a lot of dev time and reduces the friction between data engineering and data science teams. Having everything in one place also makes debugging and scaling much easier. **Official Response from Aunalisa Arellano:** > We're glad to hear that you're enjoying the comprehensive features of Databricks, including the seamless integration of data engineering, analytics, and machine learning. The collaborative notebooks and Delta Lake capabilities are designed to enhance productivity and efficiency. ### 6. Unlocking Scalable Data Insights with Databricks **Rating:** 5.0/5.0 stars **Reviewed by:** Abhi J. | Software Developer, Mid-Market (51-1000 emp.) **Reviewed Date:** July 24, 2025 **What do you like best about Databricks?** Databricks excels in unifying data engineering, analytics, and machine learning in a collaborative, cloud-based environment. Its support for multiple programming languages (Python, SQL, Scala, R) makes it incredibly flexible. The Lakehouse architecture simplifies data management by combining the best of data lakes and data warehouses. The auto-scaling compute clusters, tight integration with tools like MLflow, and powerful notebooks streamline experimentation and production deployment. I also appreciate the frequent product updates and commitment to open-source technologies like Apache Spark and Delta Lake. **What do you dislike about Databricks?** While powerful, Databricks has a learning curve—especially for non-technical users or those new to Spark-based architectures. Pricing can escalate quickly if not closely monitored, particularly with always-on clusters. The UI, although improving, still feels unintuitive in certain areas (like managing jobs or cluster permissions). Some integrations, especially with on-premise systems, require additional effort or custom workarounds. **What problems is Databricks solving and how is that benefiting you?** Databricks addresses the fragmentation between data engineering, data science, and analytics by offering a unified platform. Previously, we struggled with maintaining multiple disconnected tools for ETL, machine learning, and BI. Databricks' Lakehouse architecture allows us to manage structured and unstructured data in a single place, simplifying our data pipelines and reducing operational overhead. It also improves collaboration across teams—data engineers, analysts, and data scientists can work together in shared notebooks with version control and built-in visualizations. With Delta Lake, we now have ACID-compliant data reliability and time-travel capabilities, which help ensure data quality and reproducibility. As a result, project delivery times have decreased, and our ability to iterate quickly on models and reports has improved significantly—leading to faster business insights and better data-driven decision-making. **Official Response from Aunalisa Arellano:** > Thank you for sharing your positive experience with Databricks! We're glad to hear that you find our platform flexible, collaborative, and powerful. We appreciate your feedback and are committed to continuously improving the user experience. ### 7. Powerful Unified Platform for Data and AI, but Complex Setup and Costly for Continuous Use **Rating:** 5.0/5.0 stars **Reviewed by:** ILCHO I. | expert buyer, Airlines/Aviation, Enterprise (> 1000 emp.) **Reviewed Date:** October 16, 2025 **What do you like best about Databricks?** I like that Databricks provides a unified environment for data engineering, analytics, and machine learning. The platform makes it easy to collaborate across teams, manage large-scale data efficiently, and build advanced AI models using the same infrastructure. The integration with major cloud providers and the Lakehouse architecture make data management both flexible and scalable. **What do you dislike about Databricks?** While Databricks is a powerful and flexible platform, it can be complex to set up and manage, especially for teams without strong data engineering expertise. The cost structure can also become expensive for continuous workloads, and performance tuning sometimes requires deep knowledge of Spark and cluster optimization. Additionally, the user interface could be more intuitive for non-technical users. **What problems is Databricks solving and how is that benefiting you?** Databricks helps centralize and manage large volumes of data from different sources in a single, scalable platform. It simplifies data processing, analytics, and machine learning workflows, allowing teams to collaborate efficiently and deliver insights faster. By integrating data engineering, analytics, and AI capabilities, it reduces infrastructure complexity and accelerates the development of data-driven solutions. **Official Response from Aunalisa Arellano:** > We appreciate your positive feedback on Databricks' unified environment for data engineering, analytics, and machine learning. The integration with major cloud providers and the Lakehouse architecture are designed to provide flexibility and scalability in data management. ### 8. Great Experience with Databricks **Rating:** 5.0/5.0 stars **Reviewed by:** Brandon C. | Director, Data Science and Analytics, Enterprise (> 1000 emp.) **Reviewed Date:** May 28, 2025 **What do you like best about Databricks?** The Databricks Data Intelligence Platform allows us to have a single source of development capabilities for IT developers and business analysts. This allows for easier implementation of capabilities and consolidation of toolsets across the environment. Users are given the freedom to develop the data products they need in the time frames they need them. It makes implementation and productionalization of these projects much easier to integrate for downstream usage. **What do you dislike about Databricks?** The one "dislike" I have is that it's difficult to keep up with all of the improvements and enhancements in the platform. We always see new features to implement and want to make sure we're doing the best we can for our end users. **What problems is Databricks solving and how is that benefiting you?** Databricks is making it extremely easy for us to have a single set of tooling for multiple us cases in the data space. This allows us to be more collaborative across business units and within business units. It also allows us to have standard ways of working that can be implemented through all of the use cases. We see a lot of capabilities that can be leveraged with the platform that make repeatable capabilities easier which allows us to increase speed to market for our data products **Official Response from Aunalisa Arellano:** > We're thrilled to hear that you are enjoying the benefits of the Databricks Data Intelligence Platform, especially the ease of development and consolidation of toolsets. We understand that keeping up with new features can be challenging, and we're continuously working to improve our communication and support for our users. ### 9. Very reliable platform for modern data projects in company ! **Rating:** 4.5/5.0 stars **Reviewed by:** Arman C. | Senior consultant, Mid-Market (51-1000 emp.) **Reviewed Date:** May 20, 2025 **What do you like best about Databricks?** One thing I genuinely appreciate about Databricks is its ability to understand and adapt to our organization's specific data terminology. The platform's natural language interface makes it feel like I'm conversing with a colleague rather than navigating complex queries. Additionally, the AI-driven insights have significantly accelerated our decision making processes, allowing us to act fast on data trends. Overall its a good tool with fine customer support **What do you dislike about Databricks?** While Databricks is powerful there is definitely a learning curve when you're just getting into it. Also interface can be improved for mobile. **What problems is Databricks solving and how is that benefiting you?** We used to struggle a lot with keeping our data pipelines reliable , things would break in silos, and teams had no clear visibility. Databricks really helped us unify our data processes across departments. Now our different experts from seperate departments could easily work together . It is also helped in speeding up our model training workflows for our clients. **Official Response from Aunalisa Arellano:** > We're glad to hear that you find Databricks' ability to understand and adapt to your organization's specific data terminology valuable. Our natural language interface and AI-driven insights are designed to make data analysis more intuitive and efficient. ### 10. Centralised data management platform and excellent Ai features ! **Rating:** 4.5/5.0 stars **Reviewed by:** Anton V. | Database Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** May 20, 2025 **What do you like best about Databricks?** What i liked in Databricks is that it let us handle both raw and refined data in one go ,no need to bounce between tools. We are able to build pipelines, run analytics, and even go into ML models from the same environment. The collaborative environment was excellent for our data engineers and analysts can work in real time without being lost in getting on same page . Also, the way it connects with AWS and Azure made onboarding a lot smoother for our hybrid cloud setup. Honestly, the speed at which we can experiment and push insights to dashboards has helped us stay way more better than before. We are not just storing data anymore we’re using it intelligently without too much friction. **What do you dislike about Databricks?** While Databricks brings a lot to the table, a few things still feel clunky. The UI especially when dealing with larger clusters i do find some little lag sometimes other than that i find no major problem. **What problems is Databricks solving and how is that benefiting you?** Before Databricks we were switching between multiple tools to clean, store, and analyze data . Which slowed everything down and made collaboration tricky. Databricks pretty much merged all of that under one roof. One of the biggest wins has been the ability to process large datasets without worrying about performance bottlenecks. We’re now running real-time analytics that used to take hours, especially for sales and operations dashboards. Also, their unified platform means our data engineers, analysts, and ML folks can actually work together without throwing files back and forth. It’s helped us push insights to business teams faster, and decisions are now backed by fresher, cleaner data. **Official Response from Aunalisa Arellano:** > We're delighted to hear that Databricks has made such a positive impact on your data management and analytics processes. It's fantastic to know that the platform has improved your efficiency and collaboration. We appreciate your feedback about the UI and will strive to address any performance issues. ### 11. Databricks make enterprise scale ML project easier to manage. **Rating:** 4.0/5.0 stars **Reviewed by:** Olivia J. | Lead Machine Learning Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** May 12, 2025 **What do you like best about Databricks?** We have build a fraud detection system for a European finntech product using Databricks Data Intelligence Platform. The project required ingesting large volume of transaction data, cleaning it and training multiple machine, learning models using historical fraud patterns. Feature like tight integration with ML flow, alone helped us avoid the usual mess of managing models across Juypter notebooks and cloud storage. It’s collaborative environment allowed our ML engineers and data scientists to work together in Databricks notebooks in the same interface. Additionally, the ability to schedule retraining jobs made it easier to put a model into production with minimum effort. **What do you dislike about Databricks?** While MLflow is great, the UI for comparing runs can feel a bit outdated and lacks advanced filtering options. Managing features stores also felt slightly inefficient without more granular access control for different user roles. **What problems is Databricks solving and how is that benefiting you?** Our ML pipeline is far more stable and efficient after we implemented Databricks. We have a standardised our development workflows and now our engineers, analyst and business teams can access the same datasets and results in a single environment. This has dramatically improved our team collaboration. **Official Response from Aunalisa Arellano:** > It's great to hear that Databricks Data Intelligence Platform has helped standardize your development workflows and improve team collaboration. We aim to provide solutions that make ML pipelines more stable and efficient, and we're pleased to hear that it has benefited your team in this way. ### 12. Data Awesomeness **Rating:** 5.0/5.0 stars **Reviewed by:** Arthur G. | Director, Data Architecture, Enterprise (> 1000 emp.) **Reviewed Date:** June 10, 2025 **What do you like best about Databricks?** This makes it simple and uniform to work with data. I love how it can just be the one stop shop for data warehousing, ad hoc reporting and is my gateway to AI **What do you dislike about Databricks?** Screen real estate on a web application can be limiting. There's so much content, but you can't just pull apart sections and put them in separate windows. **What problems is Databricks solving and how is that benefiting you?** Connecting the dots between various data sources to create a comprehensive view of all our data. **Official Response from Aunalisa Arellano:** > Thank you for sharing your feedback on Databricks Data Intelligence Platform! We're thrilled to hear that you find it simple and efficient for working with data, as well as a great tool for data warehousing and AI. We appreciate your input on the screen real estate limitation and will pass this along to our development team for consideration. It's great to hear that the platform is helping you connect data sources and gain a comprehensive view of your data. If you have any further suggestions or need assistance, please feel free to reach out. We're here to help! ### 13. Transformation Journey with Databricks Data Intelligence Platform **Rating:** 5.0/5.0 stars **Reviewed by:** Deepankar B. | Senior Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** January 07, 2025 **What do you like best about Databricks?** As a data engineer who has been working with Databricks for the past two years, I can honestly say the platform has completely transformed the way we approach data engineering projects. Before Databricks, me and my team often faced challenges with managing large datasets and ensuring smooth collaboration between data engineers and data scientists. There were times when workflows felt disjointed, and troubleshooting issues across different tools consumed a lot of our time. Databricks has changed all of that. The collaborative notebooks feature, in particular, has been a game-changer. I can now work seamlessly with data scientists in real-time, troubleshooting issues and iterating on solutions much faster. For example, during a recent project, we were able to refine a machine learning model within days, thanks to the ability to easily share notebooks and quickly run experiments together. This level of collaboration used to take weeks with previous tools. The auto-scaling feature has been a lifesaver. I vividly remember struggling with performance issues when processing large datasets on our old infrastructure. Now, Databricks automatically adjusts resources based on workload, so we never have to worry about managing compute power. This has drastically cut down on processing times. For instance, a data transformation job that used to take hours now finishes in a fraction of the time, allowing us to deliver projects faster. Delta Lake has also been invaluable. Before we started using it, data consistency and quality were constant concerns, especially when dealing with large and varied data sources. Now, with Delta Lake, we can trust that our data is not only high quality but also easily accessible and queryable. One particular example was when we had to rebuild a complex dataset pipeline. Delta Lake allowed us to work with incremental data updates, making the process much more efficient and reliable. In short, Databricks has greatly reduced development time and improved the overall quality of our deliveries. It’s helped me streamline complex workflows, improve collaboration across teams, and most importantly, deliver data-driven solutions faster and with greater confidence. **What do you dislike about Databricks?** Cost Optimisation - While I appreciate the granular billing information provided, predicting costs for large projects or shared environments can still feel opaque. Many teams struggle to control runaway costs from idle clusters or suboptimal configurations. Introducing smarter autoscaling and recommendations tailored to our workloads would be invaluable. For instance, alerts for "idle clusters" or "cost hotspots" in our environment could proactively save budgets and improve efficiency. Simplified Governance and Security - Managing access at fine-grained levels can be cumbersome. For example, controlling who can view versus who can execute a notebook or job often requires workarounds. Audit logs are excellent, but making sense of them for actionable insights sometimes feels like solving a puzzle. Enhanced attribute-based access control (ABAC) and more intuitive UI-based controls for permission management would greatly streamline operations. User Experience - The collaborative notebook interface is one of Databricks' standout features, yet there are areas where it could be smoother. Collaboration is sometimes hindered when two users edit the same notebook. Version control feels basic compared to Git-based systems. Debugging within notebooks, especially for non-Python workloads, could use significant improvement. Adding inline commenting, conflict resolution tools, and robust debugging features would take the platform to the next level. A workspace-level activity feed to show what’s happening in shared projects would also be immensely helpful. Workflow Automation - Include AI-driven insights for optimizing workflows (e.g., spotting bottlenecks or inefficiencies). Enable easier integration with external workflow automation tools. **What problems is Databricks solving and how is that benefiting you?** The Databricks Data Intelligence Platform has revolutionized how I handle data challenges by providing a unified, scalable, and collaborative environment. It simplifies processing large datasets, unifies teams across workflows, and ensures robust security and governance, enabling seamless data integration and real-time insights. With tools like Delta Lake and MLflow, it has streamlined pipeline development and machine learning, significantly improving productivity and reducing time to value. By democratizing analytics for technical and non-technical users alike, Databricks fosters a truly data-driven culture. Its flexibility, performance, and end-to-end capabilities have been instrumental in driving impactful results for my organization. **Official Response from Aunalisa Arellano:** > We're delighted to hear that Databricks Data Intelligence Platform has transformed the way you approach data engineering projects. We greatly appreciate your positive feedback on the collaborative notebooks, auto-scaling, and Delta Lake features. We understand your concerns about cost optimization, governance and security, user experience, and workflow automation, and we will consider them as we work to improve our platform. Sincere thanks for taking the time to write thorough feedback about the platform—we love that you understand how Databricks fosters a data-driven culture! ### 14. Faster processing and scalability **Rating:** 5.0/5.0 stars **Reviewed by:** Yvon S. | Software Developer, Small-Business (50 or fewer emp.) **Reviewed Date:** May 08, 2025 **What do you like best about Databricks?** It's a flexible solution that works well, it's designed to distribute data. It can easily scale to handle large amounts of data and offers numerous high-level features. I like the replication features. **What do you dislike about Databricks?** It could be better if there was a more optimized user interface, it can introduce relatively high latency for operations with small files. **What problems is Databricks solving and how is that benefiting you?** It helps process larger files in a shorter period of time and supports various resources manager and engines. This product is renowned for its reliability and meets the need to process large amounts of data. **Official Response from Aunalisa Arellano:** > We're happy to hear that Databricks Data Intelligence Platform helps you process larger files in a shorter period of time and supports various resource managers and engines. Your feedback about the user interface and latency is valuable, and we will use it to enhance the user experience. ### 15. Unified Data Analytics Platform **Rating:** 4.5/5.0 stars **Reviewed by:** Sunil V. | Data Engineer L2, Mid-Market (51-1000 emp.) **Reviewed Date:** March 25, 2025 **What do you like best about Databricks?** There are so many features which I loved and some of them are unity catalog (data governance), Serverless compute (sql warehouse) and delta acid transactions (time travel in case of accidental data delete or update) **What do you dislike about Databricks?** there is nothing to say but in previously when databricks changed the UI design then little bit problem occured but now I am used to **What problems is Databricks solving and how is that benefiting you?** Its real streaming helps lot as we receive the data in near to real time and its provides all the supporting features apart from this easy to make different kind of ETL and data integration from various source **Official Response from Aunalisa Arellano:** > We're thrilled to hear that you love the unity catalog, serverless compute, and delta acid transactions features of our Data Intelligence Platform! ### 16. From raw data to actionable insights in record time **Rating:** 4.0/5.0 stars **Reviewed by:** Pierre D. | Analytics Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** January 08, 2025 **What do you like best about Databricks?** Databricks has the great ability to handle streaming data and integrate with Kafka. This is an essential feature for our organisation as we used Databricks to enhance our real time fraud detection system in the financial service sector. This has improved security and reduced fraud activities. The real time processing capabilities were also a crucial feature for our use case. Databricks also support multiple languages development, which is a key benefit for our organisation as we have both Python and Scala developers. **What do you dislike about Databricks?** During a critical phase of the project, we faced few challenges while optimising our Spark jobs. The user interface for cluster management could be improved, as we occasionally face delays when scaling clusters to handle large workloads. **What problems is Databricks solving and how is that benefiting you?** Our logistic team used Databricks to optimise delivery routes by analysing traffic patterns, fuel consumption and delivery time. By optimising all these things we almost reduced delivery time by 20% and saved significant cost. **Official Response from Aunalisa Arellano:** > It's great to hear how Databricks has helped your logistic team optimize delivery routes, leading to a significant reduction in delivery time and cost savings. We're committed to providing solutions that bring tangible benefits to our customers' operations. ### 17. Powerful open-minded data platform **Rating:** 5.0/5.0 stars **Reviewed by:** Pål d. | Principal Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 12, 2025 **What do you like best about Databricks?** Awesome tools and open mindedness, and fast innovation **What do you dislike about Databricks?** Ux still has some room for improvement to be easier to learn **What problems is Databricks solving and how is that benefiting you?** Understanding our company and build AI **Official Response from Aunalisa Arellano:** > We're glad to hear that you appreciate our powerful tools and commitment to innovation. We understand the importance of user experience and are continuously working to improve it for easier learning. Thank you for your feedback! ### 18. Databricks has unlocked ML and AI for our data **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Online Media | Mid-Market (51-1000 emp.) **Reviewed Date:** June 10, 2025 **What do you like best about Databricks?** ease of model hosting / serving and our availing to always have the latest and greatest with foundation models **What do you dislike about Databricks?** It is not very intuitive as a platform — lots of different permissions and compute is confusing **What problems is Databricks solving and how is that benefiting you?** Previously, any ML or AI was siloed off. Now we benefit from it all being in one place which makes orchestration much easier **Official Response from Aunalisa Arellano:** > It's great to hear that having ML and AI in one place has made orchestration easier for you. We're committed to solving siloed data challenges. ### 19. Data Asset version control. **Rating:** 5.0/5.0 stars **Reviewed by:** Shahid M. | Software Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** May 16, 2025 **What do you like best about Databricks?** Big data analysis typically need the version control for all data assets for simplicity , this tool have it. This is one common platform for all data assets. We can export data assets in multiple formats. **What do you dislike about Databricks?** Version interface should be more simpler for beginners and pricing is also an issue. **What problems is Databricks solving and how is that benefiting you?** Very efficient tool for sharing data with external partners and managing them. **Official Response from Aunalisa Arellano:** > We are glad to hear that you find our platform efficient for sharing data with external partners. We take note of your feedback regarding the version interface and pricing. We are dedicated to simplifying the user interface and offering competitive pricing to ensure a seamless experience for all users. ### 20. Databricks for Data analysis **Rating:** 4.5/5.0 stars **Reviewed by:** Sam G. | Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** May 19, 2025 **What do you like best about Databricks?** In this platform bulk data analysis is easy because this runs on Data intelligence engine which has generative Ai feature helps understand and process data. Databricks Assistant is very helpful. **What do you dislike about Databricks?** The interface is not good also pricing is not efficient. **What problems is Databricks solving and how is that benefiting you?** Data analysis, this tool is best and it solved bulk data analysis problem. **Official Response from Aunalisa Arellano:** > We appreciate your feedback about the interface and pricing. We are constantly working to improve the user experience and offer competitive pricing. ### 21. One of the best data insights generation tool using latest ML Technology **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** January 08, 2025 **What do you like best about Databricks?** I liked the pricing , with minimum pricing you are getting too many features and also the customer support is top notch and ready to help you in all the possible ways **What do you dislike about Databricks?** User interface needs to be betters, currently is any new person comes and see the software he gets confused, need to have easy interface **What problems is Databricks solving and how is that benefiting you?** We specially used this for getting insights from very huge database of our company, by using this software we were able to identify trends and based on those inputs only made future marketing startegy and changes in the existing product based on the customer database insights. this is really helpful softwware **Official Response from Aunalisa Arellano:** > We're thrilled to hear that you find our pricing and customer support valuable. We have noted your feedback on the user interface and will take that into consideration. Thank you for taking the time to share your thoughts! ### 22. Reiner **Rating:** 5.0/5.0 stars **Reviewed by:** Reiner D. | Analytics Architect (Microsoft), Mid-Market (51-1000 emp.) **Reviewed Date:** June 12, 2025 **What do you like best about Databricks?** The unified platform for all of data and ai **What do you dislike about Databricks?** ui is a bit in user friendly, so hope for improvements **What problems is Databricks solving and how is that benefiting you?** Data warehousing and Uc **Official Response from Aunalisa Arellano:** > We're glad to hear that you appreciate the unified platform for data and AI. We understand your feedback about the UI and are continuously working on improvements to make it more user-friendly. ### 23. Great databricks **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Mid-Market (51-1000 emp.) **Reviewed Date:** June 12, 2025 **What do you like best about Databricks?** Easy to use and best in class experience **What do you dislike about Databricks?** Nothing other than better UI UX design ‘ **What problems is Databricks solving and how is that benefiting you?** Data storage processing end to end RTL **Official Response from Aunalisa Arellano:** > It's great to hear that Databricks is helping with end-to-end data storage and processing, providing a benefit for your RTL needs. ### 24. Great **Rating:** 4.5/5.0 stars **Reviewed by:** Dipayan D. | Senior Manager, Enterprise (> 1000 emp.) **Reviewed Date:** June 12, 2025 **What do you like best about Databricks?** Agility to perform multiple tasks at the same time **What do you dislike about Databricks?** Looks and aUX change as it changes very often. **What problems is Databricks solving and how is that benefiting you?** Data modernization at all level **Official Response from Aunalisa Arellano:** > We appreciate your positive feedback on the agility of our platform for multitasking. We understand your concerns about the frequent changes in the look and feel, and we are committed to improving the user experience to provide a more stable and consistent interface. ### 25. Highly Recommended Data Intelligence platform **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** January 09, 2025 **What do you like best about Databricks?** They have very good product features and different type of Integrations and customer support is also support. your ticket will be ressolved within minutes. **What do you dislike about Databricks?** Home screen User Interface they can improve and for the first time user they can definitely add the learning or guide features **What problems is Databricks solving and how is that benefiting you?** We used this software for BDA for our business where we deal with huge database on daily basis and to find out some outcomes and patterns . which will be passed on to our data science team and after further verification we use those finding in our new product development cycle. **Official Response from Aunalisa Arellano:** > We're delighted to hear that you are satisfied with our product features, integrations, and customer support. Your feedback on the home screen user interface and onboarding process is valuable to us, and we will consider it for future enhancements. ### 26. Data analyst's go to platform ! **Rating:** 4.5/5.0 stars **Reviewed by:** Joey W. | Assosiate Database Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** October 09, 2024 **What do you like best about Databricks?** Databricks has been amazing to work on. It provides real time data collection and management through big data ML , so resourceful i would say. It combines different data from large scale data processes and make it more usable which is execellent for medium as well big enterprises.And most amazing part i like its integration with Delta lake and spark. **What do you dislike about Databricks?** It is an advance platform although it needs some improvement in ui for beginners and cost can get pretty high for working on large data. **What problems is Databricks solving and how is that benefiting you?** Databricks is very helpful in sorting out and analysis of large datasets in real time which is big thing. Scalability options are very very versatile and ai works swiftly for analysis and decision making as well. So it makes us quite productive and saves lots of time. **Official Response from Janelle Glover:** > We're glad to hear that you find Databricks Data Intelligence Platform so resourceful and beneficial for your data analysis needs. We appreciate your feedback on the UI and cost, and we'll take this into consideration at we continue to improve our platform. ### 27. Intelligence platform honest review **Rating:** 5.0/5.0 stars **Reviewed by:** Aarti V. | Software Developer, Enterprise (> 1000 emp.) **Reviewed Date:** January 08, 2025 **What do you like best about Databricks?** Everything at one place for development. Additionally, DABS will alleviate our CICD requirements. **What do you dislike about Databricks?** Dashboard monitoring feature is half baked, it need too much improvement **What problems is Databricks solving and how is that benefiting you?** For our proprietary solution ensuring data privacy and compliance is critical as well as challengeing so there databricks platform came into picture. It has plenty of features like data governance, role based access control and compliance with standards. These features are very helpful to achieve our goal **Official Response from Aunalisa Arellano:** > Thank you for sharing your feedback! We're glad to hear that you find Databricks Data Intelligence Platform helpful for development and CICD requirements. We appreciate your input on the dashboard monitoring feature and will take it into consideration for future improvements. ### 28. The best Bigdata Processing Tool **Rating:** 4.0/5.0 stars **Reviewed by:** Jessica S. | Software Consultant, Enterprise (> 1000 emp.) **Reviewed Date:** December 31, 2024 **What do you like best about Databricks?** I have used this tool for past two years , the attractive feature were faster data processing and data warehousing. i can easily intergrate it with power bi so it become easy to implement it **What do you dislike about Databricks?** I dont like the interface of this tool , and also latency issues **What problems is Databricks solving and how is that benefiting you?** My main problem was processing data from clients and upload the processed data to cloud by using this , this task became very easy **Official Response from Aunalisa Arellano:** > We appreciate your review of Databricks Data Intelligence Platform. It's great to hear that you have found the tool beneficial for faster data processing and data warehousing, as well as for integrating with Power BI. We apologize for any inconvenience caused by the interface and latency issues. Your feedback is valuable to us, and we are actively working to enhance the user interface and optimize performance. Thank you for bringing these concerns to our attention. ### 29. Databricks makes Data Intelligent **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Enterprise (> 1000 emp.) **Reviewed Date:** June 11, 2025 **What do you like best about Databricks?** Open, Integrated, and fast evolvement **What do you dislike about Databricks?** Databricks RAG service need some improvements to make more performing. **What problems is Databricks solving and how is that benefiting you?** Data cataloging with Unity catalog to help data discovery and management. AI model servings. **Official Response from Aunalisa Arellano:** > Thank you for sharing your feedback! We're glad to hear that you appreciate the open, integrated, and fast-evolving nature of our platform. We understand your concerns about the RAG service and are constantly working to improve performance. Your input is valuable in this process. ### 30. Best platform for data engineering and data science **Rating:** 4.0/5.0 stars **Reviewed by:** Asna K. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** January 07, 2025 **What do you like best about Databricks?** We used Databricks for its features such asreal time data processing and dat exploration tools for visualizing data.AutoML and Mlflow is one of the best AI integration in this platform.This software is cost efficient **What do you dislike about Databricks?** Limited tutorials for new users , not beginner freindly interface **What problems is Databricks solving and how is that benefiting you?** We used this platform analyzing and processing big data and process data from various formats, this tool is really great **Official Response from Aunalisa Arellano:** > It's great to hear that Databricks has been beneficial for analyzing and processing big data from various formats. We're pleased that the platform has been helpful for your data engineering and data science needs. ### 31. Databricks platform **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** June 12, 2025 **What do you like best about Databricks?** Based on open source, lots of certifications and materials available **What do you dislike about Databricks?** UI can be confusing at times, unclear feature naming and hierarchy **What problems is Databricks solving and how is that benefiting you?** MLOps, user management **Official Response from Aunalisa Arellano:** > Thank you for sharing your feedback! We're glad to hear that you appreciate the open source foundation and the availability of certifications and materials. Thanks for taking the time to share your thoughts. ### 32. Databricks conference 2025 **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** June 12, 2025 **What do you like best about Databricks?** All of the amazing open source features! **What do you dislike about Databricks?** User interface could be improved and made more streamlined **What problems is Databricks solving and how is that benefiting you?** It is helping me to do data migrationa **Official Response from Aunalisa Arellano:** > We're glad to hear that you appreciate the open source features of the Data Intelligence Platform! ### 33. Powerful tool to handle big data and run reports **Rating:** 5.0/5.0 stars **Reviewed by:** Sylvie P. | Consultant in Organisation & Change Management, Consulting, Small-Business (50 or fewer emp.) **Reviewed Date:** April 23, 2024 **What do you like best about Databricks?** I like this tool for running reports, managing data and it offers excellent features for analysis and visualization of query results. I liked all of that. **What do you dislike about Databricks?** It is a bit confusing at first, especially the user panel. **What problems is Databricks solving and how is that benefiting you?** In general, Databrick is used to manage different amounts of data, run queries, data science and machine learning and optimize correctly and make changes which helps us a lot to avoid delays and save time. **Official Response from Aunalisa Arellano:** > It's great to hear that Databricks Data Intelligence Platform is helping you manage different amounts of data, run queries, and optimize processes for data science and machine learning. We're committed to providing tools that help you avoid delays and save time. ### 34. Databricks has been absolute productivity tool **Rating:** 4.5/5.0 stars **Reviewed by:** Ankit R. | Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** March 19, 2023 **What do you like best about Databricks?** Databricks come with everything in one place, and that is the best thing about the platform. Now I don't have to go to EMR page to create an ERM and then create a notebook. All these can be done with just one click and one page. One gets to jump from notebooks to Query service and to AI in just one click. You get data store views, auto type suggestions based on table and schema context. All these makes the experience very smooth and fast. **What do you dislike about Databricks?** Queries get refreshed once in a while, where if some queries are not saved explicitly get deleted. There is no dark mode, hence have to use a white theme. Sometimes your queries get pushed to long queues which takes a lot of time and can be little frustrating. **What problems is Databricks solving and how is that benefiting you?** - Adhoc queries on datalake, data profiling on various schema and tables. - Creating and testing data pipelines using notebooks with various language support. - Quick, easy, and on-demand resource creation and termination. **Official Response from Aunalisa Arellano:** > We're glad to hear that you find Databricks to be a productivity tool with everything in one place. Our goal is to provide a seamless experience for our users. ## 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, 1 upvote - [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?filters%5Bsentiment_snippet%5D=1554540&qs=pros-and-cons§ion=pricing&secure%5Bexpires_at%5D=2026-08-12+11%3A22%3A24+-0500&secure%5Bsession_id%5D=e5ffec02-0010-4b1e-b139-019d790cbe82&secure%5Btoken%5D=2a49c31b88ce68d5649dee97d252f7b0e9c05176da484fcbc1d8822137cc42a2&format=llm_user) ## Databricks Integrations - 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[Azure Logic Apps](https://www.g2.com/products/azure-logic-apps/reviews) - [Azure OpenAI Service](https://www.g2.com/products/azure-openai-service/reviews) - [Azure Pipelines](https://www.g2.com/products/azure-pipelines/reviews) - [Azure Portal](https://www.g2.com/products/azure-portal/reviews) - [Azure SQL Database](https://www.g2.com/products/azure-sql-database/reviews) - [Base SAS](https://www.g2.com/products/base-sas/reviews) - [Claude](https://www.g2.com/products/claude-2025-12-11/reviews) - [Claude Code](https://www.g2.com/products/anthropic-claude-code/reviews) - [Crunchbase](https://www.g2.com/products/crunchbase/reviews) - [Dash](https://www.g2.com/products/dash-for-brands-ltd-dash/reviews) - [Datadog](https://www.g2.com/products/datadog/reviews) - [Dataiku](https://www.g2.com/products/dataiku/reviews) - [dbt](https://www.g2.com/products/dbt/reviews) - [DigitalOcean](https://www.g2.com/products/digitalocean/reviews) - [Domo](https://www.g2.com/products/domo/reviews) - [Fivetran](https://www.g2.com/products/fivetran/reviews) - 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[Microsoft SharePoint](https://www.g2.com/products/microsoft-sharepoint/reviews) - [Microsoft SQL Server](https://www.g2.com/products/microsoft-sql-server/reviews) - [Microsoft Teams](https://www.g2.com/products/microsoft-teams/reviews) - [MLflow](https://www.g2.com/products/mlflow-mlflow/reviews) - [MySQL](https://www.g2.com/products/mysql/reviews) - [ObjectWay SpA](https://www.g2.com/products/objectway-spa/reviews) - [Pega Platform](https://www.g2.com/products/pega-platform/reviews) - [PostgreSQL](https://www.g2.com/products/postgresql/reviews) - [PowerBI Portal](https://www.g2.com/products/powerbi-portal/reviews) - [Prophecy](https://www.g2.com/products/prophecy-prophecy/reviews) - [Salesforce Agentforce](https://www.g2.com/products/salesforce-agentforce/reviews) - [Salesforce Headless 360 Platform (formerly Salesforce Platform)](https://www.g2.com/products/agentforce-360-platform-formerly-salesforce-platform/reviews) - [SAP Ariba](https://www.g2.com/products/sap-ariba/reviews) - [SAP ECC](https://www.g2.com/products/sap-ecc/reviews) - 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Reports Interface - Steps to Answer - Graphs and Charts - Score Cards - Dashboards - Customizable Reports - Marketing Reports - Sales Reports - Activity Dashboard - Interactive Reports - Customizable Reports - Customizable Reports - Activity Dashboard - Customizable Dashboard **Additional Functionality** - Continuous Integration - Drag & Drop - Backup and Recovery - Multiple Programming Languages Supported - Continuous Deployment - Code Development - For No-Code Development - Version Control - Configurable Workflow - Graphical User Interface - For Low-Code Development - Activity Dashboard - Generative AI - UI Prototyping - Source Control - Software Development - API - Data Import/Export - Web App Development - Custom Development - Code Repository Integration - Data Security - Mobile Development - Access Controls/Permissions - Game Development - Collaboration Tools - Application Security - Alerts/Notifications - Automated Testing - Integrated Development Environment - Offline Access - Debugging - AI Copilot - Reporting/Analytics - Compatibility Testing - Pre-built Templates - Third-Party Integrations - Data Modeling - Customizable Branding - Data Visualization - Code Editing **Additional Functionality** - Tagging - Natural Language Processing - Data Extraction - Multi-Language - Predictive Analytics - Drag & Drop - Speech Recognition - Reporting/Analytics - Data Storage Management - Virtual Personal Assistant (VPA) - AI Copilot - Customer Segmentation - Collaboration Tools - Data Import/Export - Generative AI - For eCommerce - Role-Based Permissions - Customizable Branding - Search/Filter - Monitoring - Document Management - API - Data Visualization - Trend Analysis - Machine Learning - Access Controls/Permissions - Alerts/Escalation - Performance Metrics - Real-Time Data - Third-Party Integrations - Mobile App - Multiple Data Sources - For Sales Teams/Organizations - Sentiment Analysis - Activity Dashboard - Chatbot - Workflow Automation **Additional Functionality** - Data Cleansing - Data Extraction - Third-Party Integrations - Data Verification - Information Governance - Data Capture and Transfer - AI Copilot - Customizable Reports - Data Migration - Behavior Analytics - Real-Time Reporting - Interactive queries - Audit Trail - Multiple Data Sources - Document Storage - Access Controls/Permissions - User Management - AI/Machine Learning - Master Data Management - Task Scheduling - Data Import/Export - Monitoring - Customer Database - Audit Management - Reporting/Analytics - Data Visualization - Collaboration Tools - Workflow Management - Full Text Search - Compliance Management - Generative AI - Data Quality Control - Data Connectors - Automatic Backup - Activity Tracking - Activity Dashboard - Data Security - Data Analysis Tools - Data Synchronization - Metadata Management - Dashboard Creation - Visual Analytics - Secure Data Storage - Data Integration - Database Support **Additional Functionality** - Code Generation - Text to Image - Generative AI - API - Natural Language Processing - Virtual Characters and Avatars - Content Generation - Personalization and Recommendation - Conditional Generation - Transformer Model - Automated Image & Video Editing - Interactive and Co-Creative Systems - Text Summarization - Data Augmentation - Variation Autoencoder Models - Adversarial Training - Transfer Learning and Fine-tuning - Simulation and Scenario Generation - Creative Design - AI Copilot - Prompt Engineering - Foundation Model **Administration** - Data Modelling - Recommendations - Workflow Management - Dashboards and Visualizations - Configurable Workflow - Rules-Based Workflow **Management** - Reporting - Auditing **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **System** - Data Ingestion & Wrangling - Real-Time Data **Data Preparation** - Connectors - Data Governance **Data Management** - Data Integration - Data Compression - Data Quality - Built-In Data Analytics - In-Database Machine Learning - Data Lake Analytics - ETL - Extract Transfer Load - Data Capture and Transfer - Real-Time Analytics - Reporting/Analytics **Management** - Business Glossary - Data Discovery - Data Profililng - Reporting and Visualization - Data Lineage - Data Visualization **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **Reports** - Reports Interface - Share Reports - Steps to Answer **Data Management** - Data Integration - Metadata - Self-service - Automated workflows **Functionality** - Ease of Use - File Management - Multi-Language Support - Customization - Straight-Out-the-Box Functionality - Help Guides - Patching & Updates - Workflow Management - Change Management - Deployment Management - Performance Management - Compliance Management - Lifecycle Management - Task Management - Document Management - Database Support **Generative AI** - AI Text Generation - AI Text Summarization - Generative AI **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 - API Security - Data Security - Authentication **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 **Configuration** - Application Performance - Orchestration - Database Monitoring - Anomaly Detection - Network Security **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training - Database Support - Multi-Language **Database** - Real-Time Data Collection - Data Distribution - Data Lake **Data Transformation** - Real-Time Analytics - Data Querying - Reporting/Analytics - Predictive Analytics - Visual Analytics **Compliance** - Sensitive Data Compliance - Training and Guidelines - Policy Enforcement - Compliance Monitoring - Real-Time Monitoring **Functionality** - Extraction - Transformation - Loading - Automation - Scalability - Non-Relational Transformations - Data Extraction **Management** - Cataloging - Monitoring - Governing - Model Registry **Model Development** - Feature Engineering **Data Modeling and Blending** - Data Querying - Data Filtering - Data Blending - Data Capture and Transfer **Integration** - AI/ ML Integration - BI Tool Integration - Data lake Integration **Security** - Access Control - Roles Management - Compliance Management - Deletion Management - Access Controls/Permissions - User Management - Process Management - Audit Management - Metadata Management **Operations** - Metrics - Infrastructure management - Collaboration **Visualization** - Graphs and Charts - Score Cards - Dashboards - Formats - Mobile Dashboards - Public Dashboards - Private Dashboards **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 - Multimedia Support - Multi-Modal Input Support **Governance & Observability - AI Gateways** - Data Privacy - Cost Tracking - Centralized API Key Security **Additional Functionality** - Data Mapping - Monitoring - Charting - Integration Management - Reporting/Analytics - Ad hoc Analysis - Access Controls/Permissions - API - Match & Merge - Real-Time Monitoring - Metadata Management - Pipeline Management - Job Scheduling - Dashboard Creation - Data Storage Management - Multiple Data Sources - Data Import/Export - Generative AI - Data Quality Control - Data Connectors - Customizable Reports - Single Sign On - Version Control - Visual Analytics - Accounting Integration - Real-Time Data - eCommerce Management - AI Copilot - CRM - Data Visualization - SSL Security - Search/Filter - Real-Time Analytics - Data Capture and Transfer - Collaboration Tools - Performance Management - Data Synchronization - Drag & Drop - Data Replication - Activity Dashboard - Database Support - Workflow Management - Alerts/Notifications - Predictive Analytics - Data Migration - Third-Party Integrations - Reporting & Statistics - Data Analysis Tools **Database Administration** - Provisioning - Governance - Auditing **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 **Maintainence** - Data Quality Management - Policy Management - Data Storage Management **Management** - Cataloging - Monitoring - Governing **Data Updates** - Historical Snapshots - Real-Time Updating **Monitoring and Management** - Data Observability - Testing capabilities **Generative AI** - AI Text Generation - AI Text Summarization - Generative AI **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 **Availability** - Scalability - Backup - Archiving - Indexing **Deployment** - Managed Service - Application - Scalability **Platform** - Machine Scaling - Data Preparation - Spark Integration **Connectivity** - Hadoop Integration - Spark Integration - Multi-Source Analysis - Data Lake - Real-Time Data - Data Capture and Transfer - Trend Analysis - What-if Analysis - Statistical Analysis - Data Blending - Ad hoc Analysis - Third-Party Integrations **Security** - Data Masking - Authentication And Single Sign-On - Data Anonymization **Performance ** - Scalability **Collaboration** - Sharing - Co-Editing - Devices **Cloud Deployment** - Hybrid cloud support - Cloud migration capabilities **Generative AI** - AI Text Generation - AI Text Summarization **Generative AI** - AI Text Generation - AI Text Summarization - Generative AI **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 - Third-Party Integrations **Agentic AI - Analytics Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making - Third-Party Integrations **Additional Functionality** - Customizable Reports - Collaboration Tools - Data Extraction - Semantic Search - Data Storage Management - Ad hoc Reporting - Reporting/Analytics - Predictive Analytics - Activity Dashboard - Access Controls/Permissions - Visual Analytics - Data Mapping - Data Synchronization - Statistical Analysis - Categorization/Grouping - Trend Analysis - Data Profiling - Linked Data Management - Data Visualization - API - Multiple Data Sources - Sentiment Analysis - Search/Filter - Data Import/Export - Data Capture and Transfer - AI Copilot - Monitoring - Data Connectors - Ad hoc Analysis - Text Mining - Reporting & Statistics - Predictive Modeling - Real-Time Analytics - Configurable Workflow - Tagging - Endpoint Management - No-Code - Data Preparation - Auditing - Big Data Analytics - ML Algorithm Library - Data Management - Activity Tracking - Data Security - Workflow Management **Additional Functionality** - Version Control - Scalability - Personalization - Data Extraction - Webhooks - API - Natural Language Processing - Fallback Handling - Drag & Drop - Multiple LLM Models - Built-in AI Assistant - Automated Testing - Data Governance - Collaboration Tools - Pre-built Templates - Agent Design Tools - Deep Learning - Model Training - Analytics - Single Sign On - Debugging - Deployment Management - Proactive Error Detection **Self Service ** - Calculated Fields - Data Column Filtering - Data Discovery - Search - Collaboration / Workflow - Automodeling - Natural Language Search - Visual Discovery - Data Blending - Data Blending **Processing** - Cloud Processing - Workload Processing **Operations** - Data Visualization - Data Workflow - Governed Discovery - Embedded Analytics - Notebooks - Data Discovery **Data Management** - Data Replication - Advanced Data Analytics **Security** - Data Governance - Data Security **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image - Generative AI **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 - Third-Party Integrations - Active Directory Integration **Deployment & Integration - Analytics Platforms** - No-code Dashboard Builder - Report Scheduling and Automation - Embedded Analytics and White-labeling - Data Source Connectivity - Multiple Data Sources - Query Builder **Additional Functionality** - AI Copilot - Reporting & Statistics - Data Migration - Archiving & Retention - Data Capture and Transfer - Audit Trail - Data Synchronization - Single Sign On - Customizable Reports - Data Profiling - Authentication - Role-Based Permissions - Tagging - Secure Data Storage - Data Security - HIPAA Compliant - SSL Security - Risk Assessment - Data Mapping - Search/Filter - Self Service Portal - Multiple Data Sources - Document Storage - API - Activity Tracking - Automatic Backup - Visual Analytics **Additional Functionality** - Data Warehousing - Drag & Drop - Activity Dashboard - Data Connectors - Ad hoc Reporting - Customizable Reports - Alerts/Escalation - Templates - Forecasting - Data Migration - Data Transformation - Access Controls/Permissions - API - Data Cleansing - Data Synchronization - AI Copilot - Dashboard Creation - Data Extraction - Data Security - SSL Security - Collaboration Tools - No-Code - High Volume Processing - Database Support - Search/Filter - Generative AI **Advanced Analytics** - Predictive Analytics - Data Visualization - Big Data Services - Real-Time Analytics - Reporting/Analytics - Real-Time Analytics - Reporting/Analytics - Visual Analytics **Generative AI** - AI Text Generation - AI Text Summarization - Generative AI **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 - Third-Party Integrations **Performance & Scalability - Analytics Platforms** - Large data handling and Query Speed - Concurrent User Support - Database Support **Additional Functionality** - Parallel Processing - Ad hoc Analysis - Multiple Data Sources - API - In-Database Processing - Monitoring - Real-Time Reporting - Data Synchronization - Real-Time Monitoring - Data Connectors - Performance Metrics - Ad hoc Reporting - Alerts/Notifications - Access Controls/Permissions - Drag & Drop - Data Visualization - Data Import/Export - Match & Merge - Data Transformation - Secure Data Storage - Data Extraction - AI Copilot - Customizable Reports - Activity Dashboard - Data Migration - In-Memory Processing - Data Mapping **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 - Ad hoc Query - Visual Analytics **Building Reports** - Data Transformation - Data Modeling - WYSIWYG Report Design - Integration APIs - Real-Time Data - Real-Time Data - Third-Party Integrations - Third-Party Integrations **Platform** - Mobile User Support - Customization - User, Role, and Access Management - Internationalization - Sandbox / Test Environments - Performance and Reliability - Breadth of Partner Applications - Mobile Access - Metadata Management **Data Updates** - Historical Snapshots - Real-Time Updating - Scheduled/Automated Reports - Customizable Reports - Predictive Analytics - Data Management - Real-Time Data **Additional Functionality** - Drag & Drop - Secure Data Storage - Data Import/Export - Customizable Branding - Dashboard Creation - Access Controls/Permissions - Real-Time Reporting - Metadata Management - Forecasting - Data Storage Management - Ad hoc Analysis - Ad hoc Reporting - Data Migration - AI Copilot - Self Service Data Preparation - Search/Filter - Data Mapping - Monitoring - Sentiment Analysis - User Management - Sales Trend Analysis - Charting - Reporting & Statistics - Performance Metrics - Alerts/Notifications - Data Extraction - Widgets - Storytelling - Trend Analysis - Collaboration Tools - Financing Management - Self-service Analytics - KPI Monitoring - Dashboard - API - Data Integration - Scorecards - Data Management - Task Management - Progress Tracking - Data Connectors - Data Visualization - Profitability Analysis - Project Tracking - Strategic Planning - Goal Setting/Tracking - Publishing/Sharing - Predictive Analytics - Real-Time Monitoring - Templates - Mobile Access - Customizable Templates - Workflow Management - Financial Reporting - Audit Management - OLAP - Single Sign On - Data Synchronization **Additional Functionality** - Customizable Branding - Natural Language Processing - Data Extraction - AI Copilot - Ad hoc Reporting - Real-Time Reporting - Publishing/Sharing - Collaboration Tools - Strategic Planning - Self Service Data Preparation - Trend Analysis - Text Analysis - Real-Time Monitoring - Data Synchronization - Widgets - Benchmarking - Performance Metrics - Data Mapping - Generative AI - Trend/Problem Indicators - Customizable Templates - Access Controls/Permissions - Data Import/Export - Profitability Analysis - OLAP - Alerts/Notifications - Search/Filter - Drag & Drop - Data Connectors - Multiple Data Sources - Key Performance Indicators - Dashboard Creation - Role-Based Permissions - Data Mining - Forecasting - Ad hoc Query **Additional Functionality** - KPI Monitoring - Secure Data Storage - Multiple Data Sources - Data Visualization - Single Sign On - Natural Language Search - Search/Filter - Alerts/Notifications - AI Copilot - Real-Time Notifications - Collaboration Tools - Widgets - Performance Metrics - Ad hoc Reporting - Activity Tracking - Reporting/Analytics - Customizable Branding - Data Aggregation - Dashboard Creation - Data Connectors - Customizable Templates - Data Synchronization - API - Forecasting - Interactive Elements - Single Page View - Data Import/Export - Drag & Drop - Access Controls/Permissions - Trend Analysis - Workflow Management - Third-Party Integrations - Functions/Calculations - Historical Reporting - Data Capture and Transfer - Visual Discovery - Real-Time Updates - Real-Time Reporting - Data Mapping - Relational Display - Visual Analytics - OLAP - Ad hoc Query - Reporting & Statistics ## 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) - 4.6/5.0 (714 reviews) - [Teradata Autonomous Knowledge Platform](https://www.g2.com/products/teradata-autonomous-knowledge-platform/reviews) - 4.3/5.0 (356 reviews)