Best Big Data Analytics Software - Page 2

How Many Big Data Analytics Software Products Does G2 Track?

Total Products under this Category: 206

Category Stats (Nov 2026)

  • Average Rating: 4.48/5 (↓0.01 vs Oct 2026) The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Cloudera (+0.24%) - Among all products in this category, Cloudera recorded the largest rating increase compared to last month

Last updated: November 01, 2026

How Does G2 Rank Big Data Analytics Software Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 12,300+ Authentic Reviews
  • 206+ 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 Splunk Enterprise.

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=splunk-enterprise)

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: 4.3/5.0

Total Reviews: 139

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: 8.6/10)
  • Real-Time Analytics: 8.9/10 (Category avg: 8.6/10)
  • Data Workflow: 7.9/10 (Category avg: 8.6/10)

Who Is the Company Behind Confluent?

  • Seller: IBM
  • Company Website:
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM

Who Uses This Product?

  • Who Uses This: Senior Software Engineer, Software Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 37% Large, 33% Small

What Do G2 Reviewers Say About Confluent?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the simplified real-time data integration with Confluent's managed cloud services and scalable architecture.
  • Users appreciate the simplicity and scalability of Confluent's cloud services, enhancing real-time data integration effectively.
  • Users praise the wide range of connectors in Confluent, which simplify real-time data integration significantly.
  • Users appreciate the effortless real-time data integration provided by Confluent's simple UI and extensive connectors.
  • Users appreciate the ease of use of Confluent, enjoying effortless real-time data integration and management.
Cons
  • Users find the cost estimation challenging as prices rise with data volume, impacting overall value perception.
  • Users find the pricing increases with data volume, making it costly as they scale their usage of Confluent.
  • Users face initial difficulties with a steep learning curve and limited features in lower-priced editions of Confluent.
  • Users are frustrated with the lack of features in lower editions, contributing to a steep learning curve.
  • Users find the steep learning curve of Confluent requires significant time investment to fully grasp its workflow.

What Are Recent G2 Reviews of Confluent?

What Are G2 Users Discussing About Confluent?

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: 755

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: 8.6/10)
  • Real-Time Analytics: 8.7/10 (Category avg: 8.6/10)
  • Data Workflow: 8.9/10 (Category avg: 8.6/10)

Who Is the Company Behind MATLAB?

  • Seller: MathWorks
  • Year Founded: 1984
  • HQ Location: Natick, MA
  • LinkedIn® Page: www.linkedin.com
    8,040 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 find MATLAB's ease of use refreshing, enabling quick transitions from ideas to effective solutions with minimal setup.
  • Users appreciate the strong mathematical capabilities of MATLAB, enhancing effectiveness for data analysis and visualization tasks.
  • Users value the powerful data visualization capabilities of MATLAB, enabling clear and professional presentation of complex results.
  • Users value the variety of tools in MATLAB, which enhances productivity in mathematical modeling and data analysis.
  • Users highly value the effective simulation capabilities of MATLAB, enabling seamless and accurate results in engineering tasks.
Cons
  • Users find MATLAB's high licensing costs a significant barrier, especially for individuals and small companies.
  • Users experience slow performance in MATLAB, particularly on less powerful machines with large datasets or complex simulations.
  • Users highlight the high system requirements of MATLAB, leading to slower performance on less powerful machines.
  • Users find the expensive licensing of MATLAB prohibitive, particularly for individuals and smaller organizations seeking access.
  • Users report lagging performance with MATLAB, especially when testing large scale applications, hindering effectiveness and usability.

What Are Recent G2 Reviews of MATLAB?

What Are G2 Users Discussing About MATLAB?

EXASOL

Exasol is the world’s ​most powerful Analytics Engine, ​purpose-built to handle the most demanding data workloads at an unmatched price / performance ratio​. In-memory architecture Want to process 3 billion rows in 3 seconds, not 3 hours? Exasol manages memory cache automatically, only bringing what's needed into the database for dramatically faster access times. Automatic query tuning Enjoy optimized performance while minimizing data administration overhead. Exasol uses intelligent, proprietary algorithms to self-tune queries on the fly -- adding and removing indices automatically – so you can bring true self-service BI to your organization. User defined functions (UDF) When you need more than a SQL statement, UDF scripts allow you to program your own analysis. Take your unique machine learning and data ingest scripts written in Python, R, and Lua, and run them in our database engine. Through UDF scripts, you'll get a highly flexible interface for nearly every requirement, allowing you to bring in data quickly from wherever it lives. In addition to being the fastest, Exasol also leads in the TPC price-performance metrics, meaning everyone in your organization can take advantage of unrivaled in-memory speed at a low price. And, unlike our competitors, Exasol allows you to choose the deployment destination. Deploy in the cloud, on-premises, or hybrid to meet your organization's unique needs and preferred vendors.

Average Rating: 4.7/5.0

Total Reviews: 23

How Do G2 Users Rate EXASOL?

  • Has the product been a good partner in doing business?: 9.7/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 9.2/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 9.6/10 (Category avg: 8.6/10)
  • Data Workflow: 6.7/10 (Category avg: 8.6/10)

Who Is the Company Behind EXASOL?

  • Seller: EXASOL
  • Year Founded: 2000
  • HQ Location: Nurnberg, Bayern
  • LinkedIn® Page: www.linkedin.com
    223 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 39% Large, 32% Medium

What Do G2 Reviewers Say About EXASOL?

AI-generated summary from verified user reviews

Pros
  • Users rave about the unparalleled query performance of EXASOL, delivering results in under one second.
  • Users commend the unmatched query efficiency of EXASOL, achieving rapid results even with vast data sets.
  • Users value the unparalleled query performance of EXASOL, enabling efficient analytical processing and custom workloads.
  • Users find EXASOL to be cost-effective, offering great performance with minimal administrative overhead.
  • Users commend the fast and competent customer support, enhancing their experience with EXASOL's powerful features.
Cons
  • Users experience query execution complexity with Exasol's optimizer, but can use workarounds to enhance performance.
  • Users find the lack of a good debugger in EXASOL challenging, particularly when setting code breakpoints in Python.
  • Users find the difficult setup of EXASOL to be more time-consuming and complex than typical cloud databases.
  • Users face challenges due to limited visualization, requiring more effort for setup and fewer SQL functions available.
  • Users report performance issues with Exasol's optimizer occasionally selecting ineffective execution plans for complex queries.

What Are Recent G2 Reviews of EXASOL?

What Are G2 Users Discussing About EXASOL?

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ILUM

Ilum: A Data Platform Built by Data Engineers, for Data Engineers Ilum is a Data Lakehouse platform that unifies data management, distributed processing, analytics, and AI workflows for AI engineers, data engineers, data scientists, and analysts. It belongs to the Data Platform, Data Lakehouse, and Data Engineering software categories and supports flexible deployment across cloud, on-premise, and hybrid environments. Ilum enables technical teams to build, operate, and scale modern data infrastructure using open standards. It integrates tools for batch processing, stream processing, notebook-based exploration, workflow orchestration, and business intelligence, All In a Single Platform. Ilum supports modern open table formats like Delta Lake, Apache Iceberg, Apache Hudi, and Apache Paimon. It also offers native integration with Apache Spark and Trino for compute, with Apache Flink support currently in development. Key features include: - SQL Editor: Query Delta, Iceberg, Hudi, or Spark SQL with autocomplete, result previews, and metadata inspection. - Data Lineage & Catalog: Visualize data flow using OpenLineage and explore datasets through a searchable Data Catalog. - Notebook Integration: Use built-in Jupyter notebooks pre-wired to Spark, metadata, and your data environment for exploration or modeling. - Spark Job Management: Submit, monitor, and debug Spark jobs with integrated logs, metrics, scheduling, and a built-in Spark History Server. - Trino Support: Run federated queries across multiple data sources using Trino directly from within Ilum. - Declarative Pipelines: Define repeatable ETL and analytics pipelines, with dependency tracking and recovery logic. - Automatic ERD Diagrams: Instantly generate ER diagrams from schemas to aid in data understanding and onboarding. - ML Experimentation & Tracking: Includes MLflow for managing experiments, tracking parameters, metrics, and artifacts, fully integrated with notebooks and data pipelines to streamline model development workflows. - AI Integration & Deployment: Supports both classical ML and modern AI use cases, including GenAI workflows, vector search, and embedding-based applications. Models can be registered, versioned, and deployed for inference within declarative pipelines. - Built-in AI Agent Interface: Ilum integrates, providing a GPT-style interface to interact with your data, trigger pipelines, generate SQL, or explore metadata using natural language, bringing GenAI capabilities directly into your data platform. - BI Dashboards: Native support for Apache Superset, with JDBC integration for Tableau, Power BI, and other BI tools. Additional highlights: - Multi-Cluster Management: Connect multiple Spark or Kubernetes clusters to scale and isolate workloads. - Fine-Grained Access Control: LDAP, OAuth2, and Hydra integration for secure, role-based access. - Hybrid Ready: Designed to replace Databricks or Cloudera in environments where cloud adoption is partial, regulated, or not possible.

Average Rating: 4.9/5.0

Total Reviews: 23

How Do G2 Users Rate ILUM?

  • Has the product been a good partner in doing business?: 9.7/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 10.0/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 10.0/10 (Category avg: 8.6/10)
  • Data Workflow: 10.0/10 (Category avg: 8.6/10)

Who Is the Company Behind ILUM?

  • Seller: Ilum
  • Company Website:
  • Year Founded: 2019
  • HQ Location: Santa Fe, US
  • LinkedIn® Page: www.linkedin.com
    5 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Telecommunications
  • Company Size: 52% Large, 35% Medium

What Do G2 Reviewers Say About ILUM?

AI-generated summary from verified user reviews

Pros
  • Users commend the user-friendly interface of ILUM, enjoying seamless integration and straightforward workflows for daily tasks.
  • Users value the seamless integration of ILUM with existing tools, enhancing workflows and increasing efficiency.
  • Users value the seamless integrations of ILUM, which enhance workflow efficiency without major overhauls required.
  • Users appreciate the setup ease of ILUM, allowing seamless integration and quick deployment in existing environments.
  • Users value the easy integrations of ILUM, allowing seamless connection with existing tools and workflows.
Cons
  • Users note the complex setup of ILUM, requiring significant initial effort and expertise for optimal configuration.
  • Users find the difficult setup of ILUM challenging, requiring expertise and experimentation to optimize configurations effectively.
  • Users find the learning curve steep for ILUM's advanced features but appreciate effective support for navigation.
  • Users note that administrative settings could be more accessible, requiring extra effort to manage effectively.
  • Users highlight the complexity of initial setup requiring deep technical knowledge and extensive documentation for configuration.

What Are Recent G2 Reviews of ILUM?

Dremio

Dremio is the pioneer of The Agentic Lakehouse—the only data platform built for agents, managed by agents. Organizations need to transform ideas into actions at unprecedented speed—Dremio delivers this agility by equipping AI agents with federated data access, unstructured data processing, and rich business context through its AI Semantic Layer. In the agentic-era, data engineering teams can’t manually tune performance for thousands of users and agents asking unpredictable questions every second. Dremio’s Agentic Lakehouse autonomously manages itself, removing undifferentiated management tasks, allowing engineers to focus on initiatives that drive business results. Dremio’s agentic lakehouse automatically optimizes queries, reorganizes data, and maintains performance at any scale. Dremio is trusted by thousands of global enterprises including Shell, TD Bank, and Michelin, and built on open standards. Dremio co-created Apache Polaris and Apache Arrow, and it's the only lakehouse built natively on Apache Iceberg, Polaris, and Arrow.

Average Rating: 4.6/5.0

Total Reviews: 65

How Do G2 Users Rate Dremio?

  • Has the product been a good partner in doing business?: 9.1/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 8.9/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 8.3/10 (Category avg: 8.6/10)
  • Data Workflow: 7.1/10 (Category avg: 8.6/10)

Who Is the Company Behind Dremio?

  • Seller: Dremio
  • Year Founded: 2015
  • HQ Location: Santa Clara, California
  • LinkedIn® Page: www.linkedin.com
    357 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Financial Services, Information Technology and Services
  • Company Size: 49% Large, 39% Medium

What Do G2 Reviewers Say About Dremio?

AI-generated summary from verified user reviews

Pros
  • Users find Dremio's ease of use exceptional, enabling fast connections to multiple data sources without extensive setup.
  • Users appreciate the easy integrations with multiple data sources, significantly enhancing data management and overall efficiency.
  • Users highlight Dremio's lightning-fast performance, enabling quick data analysis and seamless integration with multiple data sources.
  • Users value the SQL support of Dremio for its ease of use and efficient integration with various data sources.
  • Users value the efficient data management capabilities of Dremio, enhancing their ability to centralize and analyze data.
Cons
  • Users find Dremio has a steep learning curve and complicated initial setup, making it challenging for beginners.
  • Users find the customer support limited and slow, which can complicate their troubleshooting and resolution process.
  • Users find the steep learning curve of Dremio challenging, especially for those new to database management.
  • Users find the difficult setup process of Dremio to be time-consuming and overwhelming for new users.
  • Users find the documentation lacking, often resorting to outside sources for essential configuration details, wasting time.

What Are Recent G2 Reviews of Dremio?

What Are G2 Users Discussing About Dremio?

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: 8.6/10)
  • Real-Time Analytics: 8.5/10 (Category avg: 8.6/10)
  • Data Workflow: 8.9/10 (Category avg: 8.6/10)

Who Is the Company Behind IBM Cloud Pak for Data?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM
  • Phone: 1-866-277-7488

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?

Omniscope Evo

Visokio builds Omniscope Evo, complete and extensible BI software for data processing, analytics and reporting. A smart experience on any device. Start from any data in any shape, load, blend, transform and explore it, extract insights through ML algorithms, then produce interactive reports and dashboards to share your findings. Omniscope is not only an all-in-one self-service BI tool with a responsive UX on all modern devices, but also a powerful and extensible platform: you can augment data workflows with Python / R scripts and enhance reports with any JS visualisation. Whether you’re a data manager, scientist or analyst, Omniscope is your complete solution: from data, through analytics to visualisation. 🧽 Data Prep, ETL: build workflows to load, stream, blend and transform any data. 🔍 Analytics: leverage machine learning, extract insights and perform visual exploration. 📊 Visualisation: design interactive reports, publish and share your results. 📜 Extensible: augment data pipelines with your Python / R scripts, enhance reports with any JS based visualisation. 🚀 Scalable: big data preparation and live query dashboards on SQL databases. 🤝 Collaboration: multi-user synchronised edits on workflows and dashboards. 🤖 Automation API: schedule parameterised data refresh & report updates, trigger tasks, alerts, edit & query data. 💐 Universal: a fresh and smart experience on any device: Windows, Mac, Linux, Android, iOS. 🏢 Deployment: on-premises or on your cloud. Built-in user permissions / OIDC / SSO 🎨 White-label: host branded data solutions and embedded analytics

Average Rating: 4.7/5.0

Total Reviews: 21

How Do G2 Users Rate Omniscope Evo?

  • Has the product been a good partner in doing business?: 9.5/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 8.9/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 8.4/10 (Category avg: 8.6/10)
  • Data Workflow: 9.8/10 (Category avg: 8.6/10)

Who Is the Company Behind Omniscope Evo?

  • Seller: Visokio
  • Year Founded: 2002
  • HQ Location: London, GB
  • LinkedIn® Page: www.linkedin.com
    8 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Information Technology and Services
  • Company Size: 65% Small, 17% Large

What Are Recent G2 Reviews of Omniscope Evo?

What Are G2 Users Discussing About Omniscope Evo?

DIAdem

DIAdem is data management software for measurement data aggregation, inspection, analysis, and reporting. DIAdem is application software that helps engineers accelerate post-processing of measurement data. It is optimized for large data sets and includes tools to quickly aggregate and search for the data you need, view and investigate that data, transform it with engineering-specific analysis functions and share results with a powerful drag-and-drop report editor. You can use DIAdem with over one thousand data file formats by utilizing DataPlugins. You can leverage scripts written in Python or Visual Basic Script to automate your repetitive data post-processing tasks and transform your measurement data into complete, accurate, and actionable insights.

Average Rating: 4.4/5.0

Total Reviews: 40

How Do G2 Users Rate DIAdem?

  • Has the product been a good partner in doing business?: 7.5/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 8.6/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 8.5/10 (Category avg: 8.6/10)
  • Data Workflow: 9.3/10 (Category avg: 8.6/10)

Who Is the Company Behind DIAdem?

  • Seller: NI
  • Year Founded: 1976
  • HQ Location: Austin, TX
  • LinkedIn® Page: www.linkedin.com
    8,041 employees on LinkedIn®
  • Ownership: NASDAQ: NATI
  • Total Revenue (USD mm): $1,286

Who Uses This Product?

  • Top Industries: Automotive, Mechanical or Industrial Engineering
  • Company Size: 43% Small, 41% Large

What Are Recent G2 Reviews of DIAdem?

What Are G2 Users Discussing About DIAdem?

Qubole

Qubole is the open data lake company that provides a simple and secure data lake platform for machine learning, streaming, and ad-hoc analytics. No other platform provides the openness and data workload flexibility of Qubole while radically accelerating data lake adoption, reducing time to value, and lowering cloud data lake costs by 50 percent. Qubole’s Platform provides end-to-end data lake services such as cloud infrastructure management, data management, continuous data engineering, analytics, and machine learning with near-zero administration. Qubole is trusted by leading brands such as Expedia, Disney, Oracle, Gannett and Adobe to spur innovation and to transform their businesses for the era of big data. For more information, visit us at www.qubole.com.

Average Rating: 4.0/5.0

Total Reviews: 237

How Do G2 Users Rate Qubole?

  • Has the product been a good partner in doing business?: 8.1/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 8.3/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 8.0/10 (Category avg: 8.6/10)
  • Data Workflow: 7.8/10 (Category avg: 8.6/10)

Who Is the Company Behind Qubole?

  • Seller: Qubole
  • Year Founded: 2011
  • HQ Location: Santa Clara, CA
  • LinkedIn® Page: www.linkedin.com
    23 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer, Data Scientist
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 51% Large, 44% Medium

What Are Recent G2 Reviews of Qubole?

What Are G2 Users Discussing About Qubole?

Gigasheet

Gigasheet is an analytics platform purpose-built for healthcare market intelligence. Gigasheet analyzes price transparency files and payer-negotiated rates at massive scale. Used by payers, consultants, and provider organizations, Gigasheet makes it easy to explore reimbursement data, benchmark pricing across payers and regions, and identify outliers using a familiar spreadsheet interface. The platform supports billions of rows and connects directly to data warehouses, cloud storage, and flat files, enabling rapid healthcare price intelligence without burdening IT resources.

Average Rating: 4.9/5.0

Total Reviews: 22

How Do G2 Users Rate Gigasheet?

  • Has the product been a good partner in doing business?: 10.0/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 10.0/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 10.0/10 (Category avg: 8.6/10)
  • Data Workflow: 10.0/10 (Category avg: 8.6/10)

Who Is the Company Behind Gigasheet?

  • Seller: Gigasheet
  • Year Founded: 2020
  • HQ Location: Washington DC Area
  • LinkedIn® Page: www.linkedin.com
    10 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Marketing and Advertising
  • Company Size: 65% Small, 17% Medium

What Do G2 Reviewers Say About Gigasheet?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Gigasheet, enabling intuitive data analysis and quick report creation.
  • Users commend Gigasheet's intuitive usability, enabling easy data analysis with familiar features and a user-friendly interface.
  • Users highlight the excellent customer support from Gigasheet, noting its responsiveness and helpfulness.
  • Users value Gigasheet's ability to handle large datasets effortlessly, enhancing their data extraction and visualization experience.
  • Users enjoy the intuitive analysis features of Gigasheet, allowing easy access and manipulation of healthcare data.
Cons
  • Users find Gigasheet expensive due to the transition from free features to costly subscription requirements.

What Are Recent G2 Reviews of Gigasheet?

ShareInsights

Accelerite Share Insights is an end- to- end big data analytics platform that unifies different analytics operations like data processing, storage and visualization, It offer unique advantages like analytics development, managed life-cycle of analytics and future proofing.

Average Rating: 4.3/5.0

Total Reviews: 12

How Do G2 Users Rate ShareInsights?

  • Has the product been a good partner in doing business?: 8.3/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 8.3/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 8.9/10 (Category avg: 8.6/10)
  • Data Workflow: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind ShareInsights?

Who Uses This Product?

  • Company Size: 42% Medium, 33% Small

What Are Recent G2 Reviews of ShareInsights?

Apache Pig

Apache Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.

Average Rating: 3.9/5.0

Total Reviews: 20

How Do G2 Users Rate Apache Pig?

  • Has the product been a good partner in doing business?: 7.5/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 7.8/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 8.3/10 (Category avg: 8.6/10)
  • Data Workflow: 7.9/10 (Category avg: 8.6/10)

Who Is the Company Behind Apache Pig?

Who Uses This Product?

  • Top Industries: Computer Software, Internet
  • Company Size: 62% Large, 19% Medium

What Are Recent G2 Reviews of Apache Pig?

Tinybird

Tinybird is a fully managed ClickHouse® service designed for software developers and AI-native product teams by enabling them to create large-scale real-time analytics projects with minimal effort. Tinybird makes integrating the open source ClickHouse database into applications simpler, faster, and more reliable, allowing engineers to focus on feature development rather than infrastructure management. Tinybird eliminates the complexities associated with traditional database management, making it an ideal choice for teams looking to leverage the power of ClickHouse without the overhead of server maintenance and scaling concerns. The target audience for Tinybird includes software developers, data engineers, technical founders, and AI-native product teams building real-time analytics capabilities in their applications. With the increasing demand for real-time data processing, Tinybird caters to teams that need to deliver insights quickly and efficiently. Use cases for Tinybird span various industries, including SaaS, e-commerce, finance, crypto, AI, and IoT, where real-time data analysis is crucial for decision-making and operational efficiency. By providing a managed service, Tinybird allows software engineers to deploy analytics features in days rather than months, significantly accelerating project timelines. Key features of Tinybird include a hosted ClickHouse database plus managed data ingestion and API layers, which simplify the process of integrating analytics into applications. The built-in authentication tools enhance security and data privacy, with support for row-level access policies using JWTs. Free observability logs storage and querying allow users to keep tabs on usage and performance. AI-native features, including Tinybird Code - a CLI agent with deep ClickHouse expertise - plus the Tinybird MCP Server, make integrating analytics features into LLM apps simpler and more robust. Additionally, Tinybird's architecture is designed to handle scaling automatically, allowing teams to focus on their core development tasks without worrying about understanding a new database or worrying about infrastructure details. For those who desire infrastructure control, Tinybird offers self-managed deployment, for free. This unique combination of features enables users to ship data-driven features rapidly while maintaining high performance and reliability. Tinybird stands out in the real-time analytics database landscape by providing the performance of one of the world's fastest OLAP databases without the associated complexity. By abstracting the technical challenges of managing clusters and provisioning resources, Tinybird empowers teams to innovate and iterate on their products more quickly. The service's emphasis on ease of use and rapid deployment makes it an attractive option for organizations looking to harness the power of real-time analytics without the burden of extensive operational overhead. With Tinybird, users can unlock the potential of their data and drive impactful insights, all while enjoying a seamless and efficient development experience.

Average Rating: 4.1/5.0

Total Reviews: 14

How Do G2 Users Rate Tinybird?

  • Has the product been a good partner in doing business?: 10.0/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 9.6/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 9.3/10 (Category avg: 8.6/10)
  • Data Workflow: 9.0/10 (Category avg: 8.6/10)

Who Is the Company Behind Tinybird?

  • Seller: Tinybird
  • Year Founded: 2019
  • HQ Location: New York, US
  • LinkedIn® Page: www.linkedin.com
    52 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software
  • Company Size: 50% Medium, 36% Small

What Do G2 Reviewers Say About Tinybird?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Tinybird, finding it simple to integrate and develop real-time dashboards.
  • Users appreciate the accurate analytics offered by Tinybird, enhancing their ability to make informed decisions effectively.
  • Users value the easy integrations with apps like Confluent Cloud, enabling swift development of real-time dashboards.
  • Users value the ease of integration and exploration in Tinybird, making real-time analytics straightforward and efficient.
  • Users appreciate the easy integration with various apps, enhancing analytics and simplifying data management processes.
Cons
  • Users express concern over poor customer support, noting slow response times and inadequate documentation for effective usage.
  • Users note a lack of features in Tinybird, limiting integrations and hindering data flow and scalability.
  • Users experience a steep learning curve with Tinybird, making navigation and feature utilization challenging for newcomers.
  • Users experience a learning difficulty with Tinybird, facing challenges in navigation and utilizing its features effectively.
  • Users face limited customization with Tinybird, which restricts adaptability and complicates integration with other platforms.

What Are Recent G2 Reviews of Tinybird?

What Are G2 Users Discussing About Tinybird?

StarTree

StarTree Cloud is a fully-managed user-facing real-time analytics Database-as-a-Service (DBaaS) designed for OLAP at massive speed and scale. Based on Apache Pinot™, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment.

Average Rating: 4.5/5.0

Total Reviews: 29

How Do G2 Users Rate StarTree?

  • Has the product been a good partner in doing business?: 8.8/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 6.9/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 8.8/10 (Category avg: 8.6/10)
  • Data Workflow: 7.9/10 (Category avg: 8.6/10)

Who Is the Company Behind StarTree?

  • Seller: StarTree
  • Company Website:
  • Year Founded: 2019
  • HQ Location: Mountain View, California
  • LinkedIn® Page: www.linkedin.com
    111 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Financial Services
  • Company Size: 38% Small, 31% Large

What Do G2 Reviewers Say About StarTree?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the fast and efficient real-time analytics of StarTree, enhancing their ability to derive quick insights.
  • Users appreciate the fast querying capabilities of StarTree, enabling efficient real-time analytics and data exploration.
  • Users appreciate the fast real-time analytics of StarTree, enabling efficient exploration of large datasets effortlessly.
  • Users appreciate the extremely fast real-time analytics of StarTree, enabling quick insights and efficient large dataset exploration.
  • Users appreciate the efficient big data handling of StarTree, enabling real-time analytics with impressive speed and affordability.
Cons
  • Users note a steep learning curve with StarTree, particularly for new teams adapting to real-time OLAP systems.
  • Users face a complex setup that requires technical knowledge, making initial use challenging for newcomers.
  • Users find the difficult setup of StarTree challenging, particularly for those unfamiliar with Apache Pinot.
  • Users express frustration over insufficient documentation, making initial setup and configuration challenging for newcomers.
  • Users often struggle with poor documentation, finding it lacks clarity and detail for effective setup and configuration.

What Are Recent G2 Reviews of StarTree?

Gathr.ai

Gathr.ai powers AI with complete data context for higher quality intelligence. With day-zero, high-fidelity data discourse, users can get data-backed answers to the ‘why’, ‘what-if’, and ‘how do I’ questions that drive business KPIs forward. This intelligence is delivered natively on top of the organization’s existing data estate — including data warehouses, databases, federated SQL engines, and operational systems. Leading businesses across industries also rely on Gathr.ai to build high-performance data pipelines, bespoke Data+AI solutions, and action-driven analytics experiences. Built for builders, Gathr.ai delivers agility, performance, and control. It snaps into the existing stack — integrating upstream and downstream systems with no extra plumbing. It gives developers starter-kit speed and full extension freedom.

Average Rating: 4.8/5.0

Total Reviews: 33

How Do G2 Users Rate Gathr.ai?

  • Has the product been a good partner in doing business?: 10.0/10 (Category avg: 8.9/10)
  • Multi-Source Analysis: 10.0/10 (Category avg: 8.6/10)
  • Real-Time Analytics: 9.8/10 (Category avg: 8.6/10)
  • Data Workflow: 10.0/10 (Category avg: 8.6/10)

Who Is the Company Behind Gathr.ai?

  • Seller: Gathr.ai
  • Year Founded: 2022
  • HQ Location: Los Gatos, CA, US
  • LinkedIn® Page: www.linkedin.com
    46 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Associate Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 79% Medium, 21% Large

What Do G2 Reviewers Say About Gathr.ai?

AI-generated summary from verified user reviews

Pros
  • Users value the seamless integrations of Gathr.ai, enabling efficient data processing and AI application development effortlessly.
  • Users value the data management capabilities of Gathr.ai, allowing natural language access to insightful data-driven answers.
  • Users value the easy drag-and-drop interface of Gathr.ai, enabling quick creation of complex data pipelines.
  • Users appreciate the ease of use of Gathr.ai, enabling effortless data ingestion and custom ETL applications.
  • Users value the easy integrations of Gathr.ai, enabling quick setup of complex pipelines and workflows effortlessly.
Cons
  • Users face access issues due to limited native connectors, requiring them to build their own in some situations.
  • Users experience connection issues when configuring connectors for legacy systems, though support offers prompt assistance.
  • Users find the difficult setup of custom connectors in Gathr.ai requires additional effort but is manageable.
  • Users find the lack of real-time data challenging for monitoring and improving pipeline performance effectively.
  • Users find the performance optimization process challenging, particularly regarding real-time streaming and data transfer visibility.

What Are Recent G2 Reviews of Gathr.ai?

Bijou Barry
BB
Researched and written by Bijou Barry
Updated April 9, 2026