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Top 10 Big Data platforms
August 18, 2025 | Editor: Michael Stromann
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BigData platforms that allow to manage and analyze data sets so large and complex that it becomes difficult to process using traditional databases.
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Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.
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The most sophisticated, open search platform. Transform your data into actionable observability. Protect, investigate, and respond to complex threats by unifying the capabilities of SIEM, endpoint security, and cloud security.
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The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.
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Apache Spark is a fast and general engine for large-scale data processing. Run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk. Write applications quickly in Java, Scala or Python. Combine SQL, streaming, and complex analytics.
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The Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage. Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL. At the same time this language also allows traditional map/reduce programmers to plug in their custom mappers and reducers when it is inconvenient or inefficient to express this logic in HiveQL.
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Cloudera helps you become information-driven by leveraging the best of the open source community with the enterprise capabilities you need to succeed with Apache Hadoop in your organization. Designed specifically for mission-critical environments, Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts. Cloudera is your partner on the path to big data.
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Apache Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure. Cassandra offers robust support for clusters spanning multiple datacenters, with asynchronous masterless replication allowing low latency operations for all clients.
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Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. You can start small for just $0.25 per hour with no commitments or upfront costs and scale to a petabyte or more for $1,000 per terabyte per year, less than a tenth of most other data warehousing solutions.
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Teradata Aster features Teradata Aster SQL-GR analytic engine which is a native graph processing engine for Graph Analysis across big data sets. Using this next generation analytic engine, organizations can easily solve complex business problems such as social network/influencer analysis, fraud detection, supply chain management, network analysis and threat detection, and money laundering.
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Unified Data Analytics Platform - One cloud platform for massive scale data engineering and collaborative data science.
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Amazon EMR is a service that uses Apache Spark and Hadoop, open-source frameworks, to quickly & cost-effectively process and analyze vast amounts of data.
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Presto is a highly parallel and distributed query engine for big data, that is built from the ground up for efficient, low latency analytics.
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BigQuery is a serverless, highly-scalable, and cost-effective cloud data warehouse with an in-memory BI Engine and AI Platform built in.
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HDInsight is a Hadoop distribution powered by the cloud. This means HDInsight was architected to handle any amount of data, scaling from terabytes to petabytes on demand. You can spin up any number of nodes at anytime. We charge only for the compute and storage you actually use.
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Vertica offers organizations new and faster ways to store, explore and serve more data. Vertica lets organizations store data in a cost-effectively, explore it quickly and leverage well-known SQL-based tools to get customer insights. By offering blazingly-fast speed, accuracy and security, it offers operational advantages to the entire organization.
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Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage. Get faster insights without the overhead (data loading, schema creation and maintenance, transformations, etc.). Analyze the multi-structured and nested data in non-relational datastores directly without transforming or restricting the data
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Qubole is a Big Data as a Service (BDaas) Platform Running on Leading Cloud Offerings Like AWS. Qubole enables you to utilize a variety of Cloud Databases and Sources, including S3, MySQL, Postgres, Oracle, RedShift, MongoDB, Vertica, Omniture, Google Analytics, and your on-premise data
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The MapR Distribution for Apache Hadoop provides organizations with an enterprise-grade distributed data platform to reliably store and process big data. MapR packages a broad set of Apache open source ecosystem projects enabling batch, interactive, or real-time applications. The data platform and the projects are all tied together through an advanced management console to monitor and manage the entire system.
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Build, deploy, and run data processing pipelines that scale to solve your key business challenges. Google Cloud Dataflow enables reliable execution for large scale data processing scenarios such as ETL, analytics, real-time computation, and process orchestration.
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Google Cloud Dataproc is a managed Hadoop MapReduce, Spark, Pig, and Hive service designed to easily and cost effectively process big datasets. You can quickly create managed clusters of any size and turn them off when you are finished, so you only pay for what you need. Cloud Dataproc is integrated across several Google Cloud Platform products, so you have access to a simple, powerful, and complete data processing platform.
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SAP HANA converges database and application platform capabilities in-memory to transform transactions, analytics, text analysis, predictive and spatial processing so businesses can operate in real-time.
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IBM Netezza appliances - expert integrated systems with built in expertise, integration by design and a simplified user experience. With simple deployment, out-of-the-box optimization, no tuning and minimal on-going maintenance, the IBM PureData System for Analytics has the industry’s fastest time-to-value and lowest total-cost-of-ownership.
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1010data provides a cloud-based platform for big data discovery and data sharing that delivers actionable, data-driven insights quickly and easily. 1010data offers a complete suite of products for big data discovery and data sharing for both business and technical users. Companies look to 1010data to help them become data-driven enterprises.
Important news about Big Data platforms
2025. Snowflake Cortex AI now features native multimodal AI capabilities
Snowflake has introduced Cortex AI COMPLETE Multimodal, the major enhancement that brings the power to analyze images and other unstructured data directly into Snowflake’s query engine, using familiar SQL at scale. It allows to unify your structured and unstructured data more efficiently and with less complexity. It works seamlessly across Snowflake data, Iceberg tables and object storage like Amazon S3 — all without moving your data. You can also leverage Snowflake’s built-in security and governance to generate deeper, trusted insights across all types of enterprise data.
2022. Cloudera launches its all-in-one SaaS data lakehouse
Cloudera, the Hadoop-centric big data company is now putting its emphasis on becoming the unified data fabric for hybrid data platforms. The company took a next step in this direction with the launch of its Cloudera Data Platform (CDP) One data lakehouse as a service (LaaS?). This managed offering is meant to give enterprises a platform to enable self-service analytics and data access for more of their employees. The company calls it the “first all-in-one data lakehouse SaaS offering”, though Databricks, which popularized the lakehouse concept, also offers SaaS-based solutions. It makes for good marketing copy, though, and Cloudera argues that its service is the first to combine compute, storage, ML, streaming analytics and enterprise security.
2021. Firebolt raises $127M for its new approach to cheaper and more efficient big data analytics
Snowflake changed the conversation for many companies when it comes to the potentials of data warehousing. Now one of the startups that’s hoping to disrupt the disruptor, Firebolt, has raised $127 million Series B. The startup claims that its performance is up to 182 times faster than that of other data warehouses with a SQL-based system that works on academic research that had yet to be applied anywhere, around how to handle data in a lighter way, using new techniques in compression and how data is parsed. Data lakes in turn can be connected with a wider data ecosystem, and what it translates to is a much smaller requirement for cloud capacity. And lower costs.
