The Coolest Big Data System And Platform Companies Of The 2025 Big Data 100
Part 3 of CRN’s Big Data 100 takes a look at the vendors solution providers should know in the big data system and platform space.
Today’s “big data stack” includes databases, data management and integration software, and data analytics tools—all critical components of an effective operational or analytical data system. But all those technologies run on the foundational systems, including hardware servers and cloud platforms, provided by some of the IT industry’s biggest companies.
As part of the CRN 2025 Big Data 100 we’ve put together the following list of big data systems and cloud platform vendors that solution providers should be familiar with.
Many of these companies are well-known names in the channel, including Dell Technologies, Hewlett Packard Enterprise and IBM, that build the underlying hardware and software that power big data IT including analytics and data-intensive operational applications.
In the cloud, where an increasing number of businesses are launching big data projects, cloud service giants like Amazon Web Services, Microsoft Azure, Google Cloud, Databricks and Snowflake provide the platforms for those initiatives.
And many of the long-established software giants like Microsoft, Oracle and SAP provide foundational cloud systems, databases and other supporting software for big data initiatives, in addition to offering their own portfolios of data management and data analysis software.
This week CRN is running the 2025 Big Data 100 list in a series of slide shows, organized by technology category, spotlighting vendors of business analytics software, database systems, data warehouse and data lake systems, data management and integration software, data observability tools, and big data systems and cloud platforms.
Some vendors have big data product portfolios that span multiple technology categories. They appear in the slideshow for the technology segment in which they are most prominent.
Amazon Web Services
Top Executive: Matt Garman, CEO
The AWS cloud platform has become the operational IT foundation for many businesses, IT vendors and solution providers. And a huge number of companies use the cloud giant’s services to store and manage data and run their operational and analytical big data and AI workloads.
In addition to serving as a platform for other big data vendors, AWS is itself a major player in the big data space with its extensive portfolio of big data services across a range of technology categories.
The company has more than a dozen database services, for example, including the Amazon Aurora and Amazon RDS managed relational databases, the Amazon Neptune graph database and the Amazon DynamoDB managed NoSQL database.
On the data processing, integration and analytics side, the AWS portfolio includes Amazon Athena for SQL queries of S3 data, Amazon Redshift for data warehousing, AWS Lake Formation for data lakes, Amazon Kinesis for real-time streaming data and video analysis, AWS Glue for data integration and AWS Data Exchange for managing third-party data.
At the company’s AWS re:Invent 2024 event in December the company launched the next generation of its Amazon SageMaker unified platform for data, analytics and AI with new capabilities including Amazon SageMaker Unified Studio, Amazon SageMaker Lakehouse, and Amazon SageMaker Data and AI Governance.
Databricks
Top Executive: Ali Ghodsi, CEO
Fast-growing Databricks, originally a pioneer in the data lakehouse space, has grown to become one of the industry’s leading big data and AI technology and service providers with its Databricks Data Intelligence Platform.
At the company’s Data + AI Summit event last year Databricks launched Lakeflow, a unified, intelligent data engineering system that combines all aspects of data engineering including data ingestion, transformation and orchestration.
The company also debuted Databricks AI/BI, a next-generation business intelligence system that aims to bring data analytics and insight to a wider audience of business users with dashboards and a conversational interface for using natural language for ad-hoc and follow-up queries.
In January Databricks, which remains privately held, stunned the industry when it announced that it had raised $15 billion in a financing round that put the company’s value at $62 billion.
Dell Technologies
Top Executive: Michael Dell, Founder, Chairman, CEO
Dell Technologies provides the servers, storage systems and other IT infrastructure systems that many businesses rely on to run their operational and analytical big data and AI workloads.
Earlier this month Dell introduced advancements across its infrastructure portfolio, including innovations to its servers, storage and data protection offerings, to help businesses achieve data center modernization.
But Dell is more than hardware. The company assembles complete systems such as the Dell Data Lakehouse and Dell Data Lakehouse for AI that combines Dell’s AI-optimized hardware and full software stack with a powerful query engine from Starburst Data.
Google Cloud
Top Executive: Thomas Kurian, CEO
Many businesses and IT vendors rely on the Google Cloud Platform (GCP) for running their big data applications and workloads.
Google Cloud offers its own expansive portfolio of big data services. In the database arena, offerings span relational, nonrelational and vector databases including the company’s Cloud SQL relational database and AlloyDB for PostgreSQL.
On the data analytics side Google’s lineup include the BigQuery data warehouse, Dataflow for streaming analytics, Analytics Hub for exchanging data analytics assets, Cloud Data Fusion for data integration and managing data pipelines, and the Looker platform for business intelligence, data applications and embedded analytics.
Hewlett Packard Enterprise
Top Executive: Antonio Neri, President, CEO
Hewlett Packard Enterprise offers a range of servers, data storage systems and other products that form the foundation for on-premises, private cloud and public cloud big data operations.
The cornerstone of HPE’s big data portfolio is HPE Ezmeral, a collection of software for data, AI and generative AI management across hybrid cloud environments. The suite includes Ezmeral Data Fabric, which simplifies data management by unifying data from various sources into a single database, and Ezmeral Unified Analytics for data engineering, data science and data analytics tasks.
HPE also provides HPE GreenLake Big Data, part of the company’s GreenLake edge-to-cloud offerings, in a complete workload system for the Apache Hadoop life cycle that includes hardware, software and services.
IBM
Top Executive: Arvind Krishna, Chairman, CEO
IBM’s “big” hardware, including mainframe computers, servers, data storage and other systems, are the foundation for many customers’ big data operations—either within a data center or in the cloud.
Beyond its system offerings, IBM offers a comprehensive lineup of big data software and services at all levels of the big data stack.
The IBM Business Analytics Enterprise platform provides reporting, data analytics, predictive analytics and data integration capabilities. The system incorporates a number of IBM products and tools including IBM Planning Analytics and IBM Cognos Analytics, IBM Watson Studio for data science and AI, IBM SPSS Statistics for statistical analysis, IBM InfoSphere Optim for data governance and life-cycle management, and IBM Watson Discovery for text analysis.
Other offerings include IBM Cloud Pak for Data for collecting, organizing and analyzing cloud-based data from any source. IBM InfoSphere Information Server handles a range of data chores from data integration to data quality and governance. And IBM Netezza Performance Server is the company’s data warehouse offering.
Earlier this month IBM Consulting moved to expand its data transformation service lineup with the acquisition of Hakkoda, a global data and AI consultancy. In February IBM struck a deal to buy DataStax and its cloud database development platform to expand the capabilities of the IBM Watsonx AI portfolio.
Microsoft
Top Executive: Satya Nadella, Chairman, CEO
Microsoft is one of the leading cloud hyperscalers with its Microsoft Azure cloud computing services, which serves as the big data platform for many customers, IT vendors and solution providers.
The software giant also offers a broad range of its own big data management and analytics software—both on Azure and as separate products. And in recent years Microsoft has been aggressively infusing AI capabilities into those products.
Two Microsoft products are longtime mainstays in the big data space: Microsoft SQL Server is one of the most widely used relational database systems in the world, and the PowerBI data visualization and interactive dashboard software remains a popular reporting tool.
Azure is the foundation for Microsoft’s next-generation big data offerings including Microsoft Fabric for AI-powered analytics, Azure Data Lake Store, Azure Synapse Analytics, Azure Data Explorer, Azure Stream Analytics for real-time analytics and Azure Data Factory for data integration.
Oracle
Top Executive: Safra Catz, CEO
Oracle, of course, got its start with the development of its ground-breaking relational database system that remains a core component of the operational and analytical IT systems within many businesses around the world.
Today the company provides cost-optimized and high-performance versions of the current release, the Oracle Database 23ai, while the Oracle Autonomous Database is a fully managed cloud database service. Oracle also offers the MySQL open-source relational database and the NoSQL Database Cloud Service.
Beyond database software, Oracle markets the Exadata enterprise database server, built on the hardware IBM acquired when it bought Sun Microsystems in 2010, for running high-performance database workloads at scale within data centers or on the Oracle Cloud Infrastructure.
And the company says its Oracle Analytics is a complete platform for every analytics user role.
SAP
Top Executive: Christian Klein, CEO
SAP is a powerhouse with its ERP, CRM, human capital management and other enterprise applications. But those operational applications generate huge amounts of data, so it’s no surprise the company is also a major player in the big data software space with tools for data management and analytics.
SAP HANA, the company’s in-memory, column-oriented database, is a foundation of SAP systems for operational and analytical tasks.
In February the company unveiled SAP Business Data Cloud, the latest generation of its data management platform for unifying data from SAP applications and third-party systems for analytical and AI tasks. In addition to building on earlier SAP products, including Business Warehouse, Datasphere and Analytics Cloud, Business Data Cloud offers natively embedded data engineering, AI and machine learning technology through an OEM deal with Databricks.
Much of what SAP offers in big data technology is built into the SAP Business Technology Platform (SAP BTP), which combines data analytics, AI, application integration, and application development and automation in a unified environment.
Snowflake
Top Executive: Sridhar Ramaswamy, CEO
Snowflake, which got its start in 2014 as a cloud data warehouse provider, has grown into a data and AI cloud platform powerhouse. The company’s growing list of services include storing and managing large volumes of data, operating data warehouses and data lakes, and performing data analysis, data engineering and machine learning tasks.
In recent years the company has expanded its application development and hosting offerings, touting itself as a platform for building, sharing and connecting data-intensive applications, data products and AI models.
In November Snowflake struck a deal to buy Datavolo and its technology for creating and managing multi-modal data pipelines for enterprise AI tasks.
For its fiscal 2025 ended Jan. 31, 2025, Snowflake reported total revenue of $1.21 billion, up more than 35 percent from $898.6 million in fiscal 2024.
