Best Big Data Platforms

Compare the Top Big Data Platforms as of October 2025

What are Big Data Platforms?

Big data platforms are systems that provide the infrastructure and tools needed to store, manage, process, and analyze large volumes of structured and unstructured data. These platforms typically offer scalable storage solutions, high-performance computing capabilities, and advanced analytics tools to help organizations extract insights from massive datasets. Big data platforms often support technologies such as distributed computing, machine learning, and real-time data processing, allowing businesses to leverage their data for decision-making, predictive analytics, and process optimization. By using these platforms, organizations can handle complex datasets efficiently, uncover hidden patterns, and drive data-driven innovation. Compare and read user reviews of the best Big Data platforms currently available using the table below. This list is updated regularly.

  • 1
    Teradata VantageCloud
    Teradata VantageCloud: Scalable Cloud Analytics and AI Platform VantageCloud is Teradata’s enterprise cloud platform built to manage the largest and most complex data ecosystems. It brings together data from across the organization, enabling advanced analytics, seamless AI deployment, and real-time insights — all within a single, scalable environment. With support for multi-cloud and hybrid deployments, VantageCloud allows businesses to manage data across AWS, Azure, Google Cloud, and on-premises systems with ease. Its open architecture ensures compatibility with modern tools and industry standards, reducing complexity and avoiding vendor lock-in. By delivering trusted AI, harmonized data, and high-performance analytics, VantageCloud equips organizations to uncover new opportunities, accelerate innovation, and make confident, data-driven decisions at scale.
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  • 2
    Google Cloud BigQuery
    BigQuery is designed to handle and analyze big data, making it an ideal tool for businesses working with massive datasets. Whether you are processing gigabytes or petabytes, BigQuery scales automatically and delivers high-performance queries, making it highly efficient. With BigQuery, organizations can analyze data at unprecedented speed, helping them stay ahead in fast-moving industries. New customers can leverage the $300 in free credits to explore BigQuery's big data capabilities, gaining practical experience in managing and analyzing large volumes of information. The platform’s serverless architecture ensures that users never have to worry about scaling issues, making big data management simpler than ever.
    Starting Price: Free ($300 in free credits)
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  • 3
    dbt

    dbt

    dbt Labs

    dbt Labs helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, analysts and engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to reduce data debt, increase trust, and accelerate insights across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence.
    Starting Price: $100 per user per user/ month
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  • 4
    DataBuck

    DataBuck

    FirstEigen

    DataBuck is an AI-powered data validation platform that automates risk detection across dynamic, high-volume, and evolving data environments. DataBuck empowers your teams to: ✅ Enhance trust in analytics and reports, ensuring they are built on accurate and reliable data. ✅ Reduce maintenance costs by minimizing manual intervention. ✅ Scale operations 10x faster compared to traditional tools, enabling seamless adaptability in ever-changing data ecosystems. By proactively addressing system risks and improving data accuracy, DataBuck ensures your decision-making is driven by dependable insights. Proudly recognized in Gartner’s 2024 Market Guide for #DataObservability, DataBuck goes beyond traditional observability practices with its AI/ML innovations to deliver autonomous Data Trustability—empowering you to lead with confidence in today’s data-driven world.
  • 5
    Domo

    Domo

    Domo

    Domo puts data to work for everyone so they can multiply their impact on the business. Our cloud-native data experience platform goes beyond traditional business intelligence and analytics, making data visible and actionable with user-friendly dashboards and apps. Underpinned by a secure data foundation that connects with existing cloud and legacy systems, Domo helps companies optimize critical business processes at scale and in record time to spark the bold curiosity that powers exponential business results.
  • 6
    Looker

    Looker

    Google

    Looker, Google Cloud’s business intelligence platform, enables you to chat with your data. Organizations turn to Looker for self-service and governed BI, to build custom applications with trusted metrics, or to bring Looker modeling to their existing environment. The result is improved data engineering efficiency and true business transformation. Looker is reinventing business intelligence for the modern company. Looker works the way the web does: browser-based, its unique modeling language lets any employee leverage the work of your best data analysts. Operating 100% in-database, Looker capitalizes on the newest, fastest analytic databases—to get real results, in real time.
  • 7
    Azure Synapse Analytics
    Azure Synapse is Azure SQL Data Warehouse evolved. Azure Synapse is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless or provisioned resources—at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.
  • 8
    Nexla

    Nexla

    Nexla

    Nexla's AI Integration platform helps enterprises accelerate data onboarding across any connector, format, or schema, breaking silos and enabling production-grade AI with Data Products and agentic retrieval without coding overhead. Leading companies, including Autodesk, Carrier, DoorDash, Instacart, Johnson & Johnson, LinkedIn, and LiveRamp trust Nexla to power mission-critical data operations across diverse environments. With flexible deployment across cloud, hybrid, and on-premises environments, Nexla meets enterprise-grade security and compliance requirements including SOC 2 Type II, GDPR, CCPA, and HIPAA. Nexla delivers 10x faster implementation than traditional alternatives, turning data challenges into competitive advantage.
    Starting Price: $1000/month
  • 9
    Qrvey

    Qrvey

    Qrvey

    Qrvey pioneered multi-tenant self-service analytics for SaaS companies and now leads the evolution toward AI-driven, autonomous analytics. With over 20 years of experience, we provide industry-leading guidance and support, ensuring our clients achieve their analytics goals. Qrvey is the partner of choice for SaaS leaders bringing AI-driven insight to their customers. About Qrvey Platform Qrvey is the embedded analytics platform designed specifically for SaaS companies. Qrvey offers insight, agility and growth. Insight for your customers · True self-service with unlimited customization · AI-driven insights · No-code workflow automation Agility for your product team · End-to-end embedded analytics platform · Native multi-tenant security · Flexible multi-cloud deployments Growth for your business · Flat-rate pricing for scale · Unmatched monetization opportunities · Embedded services
  • 10
    IBM Cognos Analytics
    IBM Cognos Analytics acts as your trusted co-pilot for business with the aim of making you smarter, faster, and more confident in your data-driven decisions. IBM Cognos Analytics gives every user — whether data scientist, business analyst or non-IT specialist — more power to perform relevant analysis in a way that ties back to organizational objectives. It shortens each user’s journey from simple to sophisticated analytics, allowing them to harness data to explore the unknown, identify new relationships, get a deeper understanding of outcomes and challenge the status quo. Visualize, analyze and share actionable insights about your data with anyone in your organization with IBM Cognos Analytics.
  • 11
    Fivetran

    Fivetran

    Fivetran

    Fivetran is a leading data integration platform that centralizes an organization’s data from various sources to enable modern data infrastructure and drive innovation. It offers over 700 fully managed connectors to move data automatically, reliably, and securely from SaaS applications, databases, ERPs, and files to data warehouses and lakes. The platform supports real-time data syncs and scalable pipelines that fit evolving business needs. Trusted by global enterprises like Dropbox, JetBlue, and Pfizer, Fivetran helps accelerate analytics, AI workflows, and cloud migrations. It features robust security certifications including SOC 1 & 2, GDPR, HIPAA, and ISO 27001. Fivetran provides an easy-to-use, customizable platform that reduces engineering time and enables faster insights.
  • 12
    Querona

    Querona

    YouNeedIT

    We make BI & Big Data analytics work easier and faster. Our goal is to empower business users and make always-busy business and heavily loaded BI specialists less dependent on each other when solving data-driven business problems. If you have ever experienced a lack of data you needed, time to consuming report generation or long queue to your BI expert, consider Querona. Querona uses a built-in Big Data engine to handle growing data volumes. Repeatable queries can be cached or calculated in advance. Optimization needs less effort as Querona automatically suggests query improvements. Querona empowers business analysts and data scientists by putting self-service in their hands. They can easily discover and prototype data models, add new data sources, experiment with query optimization and dig in raw data. Less IT is needed. Now users can get live data no matter where it is stored. If databases are too busy to be queried live, Querona will cache the data.
  • 13
    Bodo.ai

    Bodo.ai

    Bodo.ai

    Bodo’s powerful compute engine and parallel computing approach provides efficient execution and effective scalability even for 10,000+ cores and PBs of data. Bodo enables faster development and easier maintenance for data science, data engineering and ML workloads with standard Python APIs like Pandas. Avoid frequent failures with bare-metal native code execution and catch errors before they appear in production with end-to-end compilation. Experiment faster with large datasets on your laptop with the simplicity that only Python can provide. Write production-ready code without the hassle of refactoring for scaling on large infrastructure!
  • 14
    Mozart Data

    Mozart Data

    Mozart Data

    Mozart Data is the all-in-one modern data platform that makes it easy to consolidate, organize, and analyze data. Start making data-driven decisions by setting up a modern data stack in an hour - no engineering required.
  • 15
    Databricks Data Intelligence Platform
    The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
  • 16
    AtScale

    AtScale

    AtScale

    AtScale helps accelerate and simplify business intelligence resulting in faster time-to-insight, better business decisions, and more ROI on your Cloud analytics investment. Eliminate repetitive data engineering tasks like curating, maintaining and delivering data for analysis. Define business definitions in one location to ensure consistent KPI reporting across BI tools. Accelerate time to insight from data while efficiently managing cloud compute costs. Leverage existing data security policies for data analytics no matter where data resides. AtScale’s Insights workbooks and models let you perform Cloud OLAP multidimensional analysis on data sets from multiple providers – with no data prep or data engineering required. We provide built-in easy to use dimensions and measures to help you quickly derive insights that you can use for business decisions.
  • 17
    Delta Lake

    Delta Lake

    Delta Lake

    Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads. Data lakes typically have multiple data pipelines reading and writing data concurrently, and data engineers have to go through a tedious process to ensure data integrity, due to the lack of transactions. Delta Lake brings ACID transactions to your data lakes. It provides serializability, the strongest level of isolation level. Learn more at Diving into Delta Lake: Unpacking the Transaction Log. In big data, even the metadata itself can be "big data". Delta Lake treats metadata just like data, leveraging Spark's distributed processing power to handle all its metadata. As a result, Delta Lake can handle petabyte-scale tables with billions of partitions and files at ease. Delta Lake provides snapshots of data enabling developers to access and revert to earlier versions of data for audits, rollbacks or to reproduce experiments.
  • 18
    Vaex

    Vaex

    Vaex

    At Vaex.io we aim to democratize big data and make it available to anyone, on any machine, at any scale. Cut development time by 80%, your prototype is your solution. Create automatic pipelines for any model. Empower your data scientists. Turn any laptop into a big data powerhouse, no clusters, no engineers. We provide reliable and fast data driven solutions. With our state-of-the-art technology we build and deploy machine learning models faster than anyone on the market. Turn your data scientist into big data engineers. We provide comprehensive training of your employees, enabling you to take full advantage of our technology. Combines memory mapping, a sophisticated expression system, and fast out-of-core algorithms. Efficiently visualize and explore big datasets, and build machine learning models on a single machine.
  • 19
    Informatica Data Engineering
    Ingest, prepare, and process data pipelines at scale for AI and analytics in the cloud. Informatica’s comprehensive data engineering portfolio provides everything you need to process and prepare big data engineering workloads to fuel AI and analytics: robust data integration, data quality, streaming, masking, and data preparation capabilities. Rapidly build intelligent data pipelines with CLAIRE®-powered automation, including automatic change data capture (CDC) Ingest thousands of databases and millions of files, and streaming events. Accelerate time-to-value ROI with self-service access to trusted, high-quality data. Get unbiased, real-world insights on Informatica data engineering solutions from peers you trust. Reference architectures for sustainable data engineering solutions. AI-powered data engineering in the cloud delivers the trusted, high quality data your analysts and data scientists need to transform business.
  • 20
    The Autonomous Data Engine
    There is a consistent “buzz” today about how leading companies are harnessing big data for competitive advantage. Your organization is striving to become one of those market-leading companies. However, the reality is that over 80% of big data projects fail to deploy to production because project implementation is a complex, resource-intensive effort that takes months or even years. The technology is complicated, and the people who have the necessary skills are either extremely expensive or impossible to find. Automates the complete data workflow from source to consumption. Automates migration of data and workloads from legacy Data Warehouse systems to big data platforms. Automates orchestration and management of complex data pipelines in production. Alternative approaches such as stitching together multiple point solutions or custom development are expensive, inflexible, time-consuming and require specialized skills to assemble and maintain.
  • 21
    Dremio

    Dremio

    Dremio

    Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable.
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