Best Big Data Analytics Software with Governed Discovery Capabilities

How Many Big Data Analytics Software Products Does G2 Track?

Total Products under this Category: 108

Category Stats (Sep 2026)

  • Average Rating: 4.46/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Cloudera (+2.21%) - Among all products in this category, Cloudera recorded the largest rating increase compared to last month

Last updated: September 03, 2026

How Does G2 Rank Big Data Analytics Software Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 8,500+ Authentic Reviews
  • 108+ Products
  • Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

G2 Grid® for Big Data Analytics Software

G2 Grid® for Big Data Analytics Software plotting products by satisfaction and market presence

Highlighted products: Databricks, Google Cloud BigQuery, Snowflake, IBM watsonx.data, Alteryx, Azure Databricks, Kyvos Semantic Layer, and Azure Synapse Analytics.

Underlying data: [Grid® JSON](https://www.g2.com/categories/big-data-analytics/grids.json?focus%5B%5D=databricks&focus%5B%5D=google-cloud-bigquery&focus%5B%5D=snowflake&focus%5B%5D=ibm-watsonx-data&focus%5B%5D=alteryx&focus%5B%5D=azure-databricks&focus%5B%5D=kyvos-semantic-layer&focus%5B%5D=azure-synapse-analytics)

Azure Databricks

Azure Databricks is a unified, open analytics platform developed collaboratively by Microsoft and Databricks. Built on the lakehouse architecture, it seamlessly integrates data engineering, data science, and machine learning within the Azure ecosystem. This platform simplifies the development and deployment of data-driven applications by providing a collaborative workspace that supports multiple programming languages, including SQL, Python, R, and Scala. By leveraging Azure Databricks, organizations can efficiently process large-scale data, perform advanced analytics, and build AI solutions, all while benefiting from the scalability and security of Azure. Key Features and Functionality: - Lakehouse Architecture: Combines the best elements of data lakes and data warehouses, enabling unified data storage and analytics. - Collaborative Notebooks: Interactive workspaces that support multiple languages, facilitating teamwork among data engineers, data scientists, and analysts. - Optimized Apache Spark Engine: Enhances performance for big data processing tasks, ensuring faster and more reliable analytics. - Delta Lake Integration: Provides ACID transactions and scalable metadata handling, improving data reliability and consistency. - Seamless Azure Integration: Offers native connectivity to Azure services like Power BI, Azure Data Lake Storage, and Azure Synapse Analytics, streamlining data workflows. - Advanced Machine Learning Support: Includes pre-configured environments for machine learning and AI development, with support for popular frameworks and libraries. Primary Value and Solutions Provided: Azure Databricks addresses the challenges of managing and analyzing vast amounts of data by offering a scalable and collaborative platform that unifies data engineering, data science, and machine learning. It simplifies complex data workflows, accelerates time-to-insight, and enables the development of AI-driven solutions. By integrating seamlessly with Azure services, it ensures secure and efficient data processing, helping organizations make data-driven decisions and innovate rapidly.

Average Rating: 4.5/5.0

Total Reviews: 213

How Do G2 Users Rate Azure Databricks?

  • Has the product been a good partner in doing business?: 8.8/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 9.0/10 (Category avg: 8.5/10)
  • Real-Time Analytics: 8.9/10 (Category avg: 8.5/10)
  • Data Workflow: 8.7/10 (Category avg: 8.5/10)

Who Is the Company Behind Azure Databricks?

  • Seller: Microsoft
  • Year Founded: 1975
  • HQ Location: Redmond, Washington
  • Twitter: @microsoft
    13,091,739 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    231,632 employees on LinkedIn®
  • Ownership: MSFT

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 47% Large, 28% Medium

What Do G2 Reviewers Say About Azure Databricks?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Azure Databricks, enjoying seamless integration and simplified development processes.
  • Users love the continuous feature improvements in Azure Databricks, enhancing integration and performance significantly.
  • Users value the seamless integrations of Azure Databricks with Azure services, enhancing efficiency and reducing complexity.
  • Users highlight the impressive speed of Azure Databricks, facilitating efficient large-scale data processing and analytics.
  • Users appreciate the seamless integration and comprehensive analytics features of Azure Databricks for efficient data processing.
Cons
  • Users find the complexity of setup and configuration challenging, especially for newcomers navigating Azure Databricks.
  • Users find the difficult setup of Azure Databricks challenging, especially for those new to the platform.
  • Users face a steep learning curve with Azure Databricks, especially newcomers navigating its complex features and configurations.
  • Users experience slow performance with Azure Databricks, particularly with cluster startup times and parallel processing efficiency.
  • Users express concern about unclear pricing for Azure Databricks, noting unpredictable costs without careful monitoring and optimization.

What Are Recent G2 Reviews of Azure Databricks?

What Are G2 Users Discussing About Azure Databricks?

Alteryx

Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial.

Average Rating: 4.6/5.0

Total Reviews: 863

How Do G2 Users Rate Alteryx?

  • Has the product been a good partner in doing business?: 8.8/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 9.0/10 (Category avg: 8.5/10)
  • Real-Time Analytics: 8.4/10 (Category avg: 8.5/10)
  • Data Workflow: 9.2/10 (Category avg: 8.5/10)

Who Is the Company Behind Alteryx?

  • Seller: Alteryx
  • Company Website:
  • Year Founded: 1997
  • HQ Location: Irvine, CA
  • Twitter: @alteryx
    26,149 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    2,304 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Analyst, Analyst
  • Top Industries: Financial Services, Accounting
  • Company Size: 63% Large, 21% Medium

What Do G2 Reviewers Say About Alteryx?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use in Alteryx, finding it simple to automate tasks with drag and drop functionality.
  • Users value the automation capabilities of Alteryx, streamlining data processes and enhancing analytical efficiency.
  • Users find Alteryx to be very intuitive, making it easy for non-technical users to learn and utilize.
  • Users find that Alteryx's interface makes learning technology easy for everyone, even those without a tech background.
  • Users value Alteryx for its efficiency in managing data, streamlining workflows, and enhancing overall productivity.
Cons
  • Users highlight the expensive pricing of Alteryx, making it difficult for small teams or startups to afford licenses.
  • Users face a steep learning curve with Alteryx, requiring time to master its complex features.
  • Users find that Alteryx suffers from missing features, such as lack of direct database access and limited reporting tools.
  • Users find the learning difficulty of Alteryx steep, especially for those unfamiliar with RegEx and SQL.
  • Users experience slow performance with Alteryx, particularly when handling large workflows and during data wrangling tasks.

What Are Recent G2 Reviews of Alteryx?

Confluent

Today’s customers expect every digital experience to be immediate, connected, and personalized. That takes more than data at rest - it takes trusted data in motion. Confluent is the complete Data Streaming Platform for keeping data in motion from the moment business change occurs through processing, governance, and serving. Built by the original creators of Apache Kafka®, Confluent connects applications, services, and systems; processes streams in real time with Apache Flink®; and serves trusted, always-current data wherever it is needed across cloud, hybrid, and self-managed environments. With deployment options including fully managed Confluent Cloud, self-managed Confluent Platform and Brint-your-own-cloud Confluent WarpStream, teams can power event-driven applications, real-time analytics, AI, and operational workflows while choosing the operating model that fits their environment and turning live data into better customer experiences and business outcomes.

Average Rating: 4.4/5.0

Total Reviews: 111

How Do G2 Users Rate Confluent?

  • Has the product been a good partner in doing business?: 8.5/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 8.3/10 (Category avg: 8.5/10)
  • Real-Time Analytics: 8.9/10 (Category avg: 8.5/10)
  • Data Workflow: 7.9/10 (Category avg: 8.5/10)

Who Is the Company Behind Confluent?

  • Seller: IBM
  • Company Website:
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    328,202 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Senior Software Engineer, Software Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 36% Large, 33% Small

What Do G2 Reviewers Say About Confluent?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the simplicity and scalability of Confluent's managed cloud services, enhancing real-time data integration.
  • Users appreciate the effortless integration of Confluent's cloud services, enhancing their experience with Kafka and Flink.
  • Users appreciate the wide range of connectors in Confluent, enhancing real-time data integration effortlessly.
  • Users appreciate the effortless data integration offered by Confluent, enhancing real-time processing with robust tools and scalability.
  • Users appreciate the ease of use of Confluent, enjoying simplified data integration and a user-friendly interface.
Cons
  • Users note the high cost estimation with data growth and a steep learning curve for effective use.
  • Users find Confluent expensive as costs rise with data volume, and learning the system can be time-consuming.
  • Users face initial difficulties with a steep learning curve and costly pricing as data volumes increase.
  • Users find a lack of features in Confluent, especially in lower tiers, leading to increased costs and complexity.
  • Users face a steep learning curve with Confluent, requiring significant time to master its workflow and features.

What Are Recent G2 Reviews of Confluent?

What Are G2 Users Discussing About Confluent?

Cloudera

Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives. The Cloudera data and AI platform includes: Cloudera AI: Deploy and scale any AI model, anywhere. Cloudera brings compute to governed data where it lives for Private AI anywhere by design. Complete control, security, and governance of mission-critical data, models, agents, and inference ensure faster sovereign AI deployments. Cloudera Data-in-Motion: Make fast decisions from real-time data anywhere. Move data with any structure from any source to any destination seamlessly across hybrid environments, enabling in-the-moment business-critical decisions by processing and analyzing real-time data anywhere, from the edge to AI, as business happens. Cloudera Open Data Lakehouse: Process any data, anywhere, for actionable insights. Make smart decisions with an open data lakehouse powered by Apache Iceberg that delivers trusted, reliable, and unified data to fuel agents, AI applications, and analytics, improving collaboration, breaking silos, and simplifying sharing. Cloudera Unified Data Fabric: Unify security and governance across the entire data estate. Move beyond fragmented data management: Break down silos and connect disparate data sources intelligently and securely to provide a unified view of all organizational data and centralized end-to-end control across complex hybrid data environments.

Average Rating: 4.2/5.0

Total Reviews: 187

How Do G2 Users Rate Cloudera?

  • Has the product been a good partner in doing business?: 8.4/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 8.6/10 (Category avg: 8.5/10)
  • Real-Time Analytics: 7.0/10 (Category avg: 8.5/10)
  • Data Workflow: 8.0/10 (Category avg: 8.5/10)

Who Is the Company Behind Cloudera?

  • Seller: Cloudera
  • Company Website:
  • Year Founded: 2008
  • HQ Location: Santa Clara, CA
  • Twitter: @cloudera
    106,442 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    3,446 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Banking
  • Company Size: 39% Large, 35% Small

What Do G2 Reviewers Say About Cloudera?

AI-generated summary from verified user reviews

Pros
  • Users praise the user-friendly interface of Cloudera, highlighting its simplicity in managing big data efficiently.
  • Users value the easy scalability of Cloudera, enabling efficient management of large amounts of data effortlessly.
  • Users value the robust security features of Cloudera, ensuring safe and reliable data management across platforms.
  • Users value the comprehensive suite of tools in Cloudera for effective data management and analytics.
  • Users find Cloudera's scalability and centralized administration invaluable for efficient monitoring and management of data processes.
Cons
  • Users express concerns over the high costs of Cloudera, noting it's expensive for its complexity and maintenance.
  • Users find Cloudera's database to be complex, making it challenging for inexperienced professionals to utilize effectively.
  • Users find Cloudera's setup difficult to learn, particularly challenging for beginners without adequate tutorials or guidance.
  • Users find the poor documentation of Cloudera frustrating, complicating navigation and setup for complex data configurations.
  • Users often face access issues with Cloudera, particularly with unauthorized errors in Airflow tasks and limited documentation.

What Are Recent G2 Reviews of Cloudera?

What Are G2 Users Discussing About Cloudera?

Azure Data Lake Analytics

Azure Data Lake Analytics is a distributed, cloud-based data processing architecture offered by Microsoft in the Azure cloud. It is based on YARN, the same as the open-source Hadoop platform.

Average Rating: 4.2/5.0

Total Reviews: 28

How Do G2 Users Rate Azure Data Lake Analytics?

  • Has the product been a good partner in doing business?: 8.6/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 7.9/10 (Category avg: 8.5/10)
  • Real-Time Analytics: 8.1/10 (Category avg: 8.5/10)
  • Data Workflow: 8.5/10 (Category avg: 8.5/10)

Who Is the Company Behind Azure Data Lake Analytics?

  • Seller: Microsoft
  • Year Founded: 1975
  • HQ Location: Redmond, Washington
  • Twitter: @microsoft
    13,091,739 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    231,632 employees on LinkedIn®
  • Ownership: MSFT

Who Uses This Product?

  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 54% Large, 27% Medium

What Are Recent G2 Reviews of Azure Data Lake Analytics?

What Are G2 Users Discussing About Azure Data Lake Analytics?

IBM Cloud Pak for Data

IBM Cloud Pak® for Data is a fully integrated data and AI platform that modernizes how businesses collect, organize and analyze data, forming the foundation to infuse AI across their organization. Running on Red Hat OpenShift and available on any cloud, this unified platform helps companies automate the end-to-end AI lifecycle. The intelligent data fabric in IBM Cloud Pak for Data enables automated distributed queries at scale without data movement; automated discovery and understanding of business-ready data; automated universal privacy and usage policies across the data ecosystem; and optimized model training, accuracy and explainability. View the demo: https://mediacenter.ibm.com/media/1_je41fqqz. The platform delivers on the below use cases: • Data access and availability – Eliminate data silos and simplify your data landscape to enable faster, cost-effective extraction of value from your data. • Data quality and governance - Apply governance solutions and methodologies to deliver trusted, business data. • Data privacy and security - Fully understand and manage sensitive data with a pervasive privacy framework. • ModelOps - Automate the AI lifecycle and synchronize application and model pipelines to scale AI deployments. • AI governance – Ensure your AI is transparent, compliant and trustworthy with greater visibility into model development, with capabilities such as explainable AI, model risk management and bias detection. • AI for Financial Operations - Automate and integrate planning across your organization, from financial planning & analysis to workforce planning, sales forecasting and supply chain planning. • AI for Customer care - Reduce time to resolution, decrease call volume and increase customer satisfaction. IBM Watson Assistant (WA) can provide AI-powered automated assistance and enable human agents to better handle inquiries. IBM Watson Discovery (WD) complements Watson Assistant and can help unlock insights from complex business content. Discover IBM Cloud Pak for Data Industry Accelerators: https://dataplatform.cloud.ibm.com/gallery?context=cpdaas See a case study: https://mediacenter.ibm.com/media/1_sr6lx8sz Try at no-cost: http://ibm.biz/dataplatformtrial

Average Rating: 4.3/5.0

Total Reviews: 71

How Do G2 Users Rate IBM Cloud Pak for Data?

  • Has the product been a good partner in doing business?: 8.1/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 8.1/10 (Category avg: 8.5/10)
  • Real-Time Analytics: 8.5/10 (Category avg: 8.5/10)
  • Data Workflow: 8.9/10 (Category avg: 8.5/10)

Who Is the Company Behind IBM Cloud Pak for Data?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    328,202 employees on LinkedIn®
  • Ownership: SWX:IBM

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 52% Large, 27% Small

What Are Recent G2 Reviews of IBM Cloud Pak for Data?