Best Big Data Analytics Software with Embedded Analytics 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?

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?

MATLAB

MATLAB is a high-level programming and numeric computing environment widely utilized by engineers and scientists for data analysis, algorithm development, and system modeling. It offers a desktop environment optimized for iterative analysis and design processes, coupled with a programming language that directly expresses matrix and array mathematics. The Live Editor feature enables users to create scripts that integrate code, output, and formatted text within an executable notebook. Key Features and Functionality: - Data Analysis: Tools for exploring, modeling, and analyzing data. - Graphics: Functions for visualizing and exploring data through various plots and charts. - Programming: Capabilities to create scripts, functions, and classes for customized workflows. - App Building: Facilities to develop desktop and web applications. - External Language Interfaces: Integration with languages such as Python, C/C++, Fortran, and Java. - Hardware Connectivity: Support for connecting MATLAB to various hardware platforms. - Parallel Computing: Ability to perform large-scale computations and parallelize simulations using multicore desktops, GPUs, clusters, and cloud resources. - Deployment: Options to share MATLAB programs and deploy them to enterprise applications, embedded devices, and cloud environments. Primary Value and User Solutions: MATLAB streamlines complex mathematical computations and data analysis tasks, enabling users to develop algorithms and models efficiently. Its comprehensive toolboxes and interactive apps facilitate rapid prototyping and iterative design, reducing development time. The platform's scalability allows for seamless transition from research to production, supporting deployment on various systems without extensive code modifications. By integrating with multiple programming languages and hardware platforms, MATLAB provides a versatile environment that addresses the diverse needs of engineers and scientists across industries.

Average Rating: 4.5/5.0

Total Reviews: 753

How Do G2 Users Rate MATLAB?

  • Has the product been a good partner in doing business?: 8.4/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 8.4/10 (Category avg: 8.5/10)
  • Real-Time Analytics: 8.7/10 (Category avg: 8.5/10)
  • Data Workflow: 8.9/10 (Category avg: 8.5/10)

Who Is the Company Behind MATLAB?

  • Seller: MathWorks
  • Year Founded: 1984
  • HQ Location: Natick, MA
  • Twitter: @MATLAB
    105,142 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    7,985 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Student, Graduate Research Assistant
  • Top Industries: Higher Education, Research
  • Company Size: 42% Large, 31% Small

What Do G2 Reviewers Say About MATLAB?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the user-friendly interface of MATLAB, making data visualization and manipulation easy and efficient.
  • Users appreciate the powerful visualization tools of MATLAB, enhancing real-time data plotting and image processing capabilities.
  • Users appreciate the powerful and user-friendly data visualization features of MATLAB for real-time plotting.
  • Users appreciate the variety of tools in MATLAB, enhancing capabilities in numerical analysis, image processing, and simulations.
  • Users appreciate the ease of simulations with MATLAB, especially with its seamless integration of Simulink for diverse applications.
Cons
  • Users find MATLAB to be expensive, making it difficult for individuals and small companies to afford.
  • Users often experience slow performance with MATLAB, especially on less powerful machines or with large datasets.
  • Users find MATLAB's high system requirements frustrating, often leading to slower performance on less powerful machines.
  • Users find the expensive licensing of MATLAB a significant barrier, particularly for individuals and small companies.
  • Users frequently encounter lagging performance with MATLAB, especially during large simulations and with multiple scripts open.

What Are Recent G2 Reviews of MATLAB?

What Are G2 Users Discussing About MATLAB?

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?