Part 3 of CRN’s 2024 Big Data 100 includes a look at the vendors solution providers should know in the big data system and cloud platform space.

All Systems Go

Today’s “big data stack” includes databases, data management 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 biggest companies in the IT industry.

As part of the CRN 2024 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 deploying big data projects, cloud service giants like Amazon Web Services, Microsoft Azure, Google Cloud and Snowflake provide the platforms for those initiatives.

And 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 CRN 2024 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: CEO Adam Selipsky

The AWS cloud platform is the big data platform for many businesses, IT vendors and solution providers that use the cloud giant’s services to store and manage data and run their operational and analytical big data and AI workloads.

But AWS is itself a major player in the big data space its own extensive portfolio of big data services including databases (including Amazon Aurora and Amazon RDS managed relational databases and the Amazon DynamoDB managed NoSQL database); data analytics (Amazon Athena for SQL queries of S3 data, Amazon Redshift data warehousing, AWS Lake Formation for data lakes and Amazon Kinesis real-time streaming data and video analysis); and data management (AWS Glue for data integration and AWS Data Exchange for managing third-party data).

At the AWS re:Invent conference in November the company launched several new serverless products across its database and analytics portfolio that makes it easier to scale data infrastructure. Amazon Aurora Limitless Database automatically scales beyond the write limits of a single Amazon Aurora database. And the new Amazon Redshift Severless capability uses AI to predict workloads and automatically scale and optimize resources.

Dell Technologies

Top Executive: CEO Michael Dell

Dell provides the servers, storage systems and other IT infrastructure systems that many businesses and organizations rely on to run their operational and analytical big data workloads.

Earlier this month Dell expanded the capabilities of the Dell PowerEdge XE9680 server with the addition of the Intel Gaudi 3 AI accelerator, making the server a key player in the acceleration of AI and generative AI, machine learning, deep learning training and HPC modeling.

But Dell is more than hardware. The company assembles complete systems such as the recently launched Dell Data Lakehouse that combines Dell’s AI-optimized hardware and full software stack with a powerful query engine from Starburst Data.

Google Cloud

Top Executive: CEO Thomas Kurian

Many businesses and IT vendors rely on the Google Cloud Platform (GCP) for running their big data applications and workloads.

Google Cloud’s own big data services encompass the database arena including the company’s Cloud SQL relational database, Firebase NoSQL real-time database, and AlloyDB for PostgreSQL. In data analytics Google’s offerings include the BigQuery data warehouse, Dataflow streaming analytics, Analytics Hub for exchanging data analytics assets, and the Looker platform for business intelligence, data applications and embedded analytics.

At the Google Cloud Next ’24 conference earlier this month Google Cloud said it was integrating its Gemini generative AI and large language model technology into its big data offerings including BigQuery, Looker and Google databases. Adding Gemini to BigQuery provides assistance for data preparation, discovery, analysis and governance tasks, for example, while its addition to Looker creates new ways for users to engage with data and analytical results.

Hewlett Packard Enterprise

Top Executive: President and CEO Antonio Neri

Like Dell, IBM and other IT infrastructure providers, 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.

Cornerstones of HPE’s big data portfolio are the HPE Ezmeral Data Fabric, which simplifies data management by unifying data types into a single database, and Ezmeral unified analytics and AI software.

HPE also provides HPE GreenLake Big Data, part of the company’s GreenLake edge-to-cloud offerings, in a complete workload system for the Hadoop lifecycle that includes hardware, software and services.

IBM

Top Executive: CEO Arvind Krishna

IBM’s mainframe computers, servers, data storage systems and other products are the foundation for many customers’ big data tasks – either within a data center or in the cloud.

IBM also provides a comprehensive line of software at all levels of the big data stack including Cloud Pak for Data, Cognos Analytics, Databand data observability, Db2 and Db2 Big SQL databases, InfoSphere Information Server, the Netezza data warehouse system, and a number of managed database services including EnterpriseDB, MongoDB, MySQL and PostgreSQL.

IBM teams up with data platform provider Cloudera to offer a number of big data and AI services based on the two companies’ product portfolios. One example is the combination of Cloudera DataFlow and the Cloudera Data Platform with IBM Cloud Pak for Data.

Microsoft

Top Executive: CEO Satya Nadella

Microsoft is one of the leading cloud hyperscalers with its Microsoft Azure cloud computing services, the big data platform for many customers, IT vendors and solution providers.

The software giant also provides a broad range of its own big data management and analytics software – both on Azure and as separate products. And in the last year Microsoft has been aggressively infusing AI capabilities into those products.

Azure cloud offerings include Azure Synapse Analytics, Azure Data Explorer, Azure Stream Analytics for real-time analytics, Azure Data Factory for data integration, Azure Cosmos DB for AI-powered applications, and the Azure SQL line of cloud database services (including MySQL, Apache Cassandra, MariaDB Redis and PostgreSQL).

Microsoft Power BI, part of the company’s Power Platform, is the company’s flagship data analysis, data visualization and report creation software.

NetApp

Top Executive: CEO George Kurian

NetApp is best known for being the largest independent data storage manufacturer and is a mainstay of the annual CRN Storage 100. In recent years the company has gone beyond unified data storage to brand itself as an “intelligent data infrastructure” company with integrated data services.

The company’s offerings include the NetApp ONTAP data infrastructure software and NetApp BlueXP unified data management tools.

Oracle

Top Executive: CEO Safra Catz

Oracle’s flagship relational database system, currently available as the Oracle Database 19c long-term release and Oracle database 21c “innovation release,” is at the core of many operational and analytical big data systems operated by businesses and organizations.

Beyond its flagship relational database, Oracle owns the MySQL database and offers the MySQL HeatWave fully managed database-as-a-service and the Oracle NoSQL Database Cloud Service.

Oracle has its big data customers covered on both the cloud and the on-premises hardware sides. The Oracle Exadata Database machine is a pre-configured hardware/software “cloud in a box” database server with CPUs, storage and InfiniBand networking. The company also markets the Oracle Unbreakable Database Appliance targeting SMB customers.

Through the Oracle Cloud Infrastructure (OCI) the company offers big data cloud services such as databases, data integration, data streaming, data replication and data lake management. The Oracle Analytics platform and analysis tools around the Oracle Fusion cloud applications are also offered through OCI.

SAP

Top Executive: CEO Christian Klein

SAP is best known for its ERP, CRM, human capital management and other enterprise applications. But with those operational applications generating huge amounts of data, the Waldorf, Germany-based 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 key component of SAP systems for both operational and analytical tasks.

Much of what SAP offers in big data technology today is built into the SAP Business Technology Platform (SAP BTP), a system that combines data analytics, AI, application development and automation, application integration, and extended planning and analysis – all in a unified environment.

Specific products within SAP BTP include SAP Analytics Cloud, SAP Master Data Governance, and the SAP Datasphere unified service for data integration, data cataloging, data warehousing, semantic modeling and workload virtualization across SAP and non-SAP data. In March SAP bolstered Datasphere with new knowledge graph capabilities and integrated its Joule copilot with the system.

Snowflake

Top Executive: CEO Sridhar Ramaswamy

Since its 2014 launch data cloud company Snowflake has grown beyond its initial focus on cloud data warehousing services to become a comprehensive data cloud platform for storing and managing big data, operating data warehouses and data lakes, and performing data analysis, data engineering and machine learning tasks.

More recently the company has been expanding its application development and hosting offerings, touting itself as a platform for data-intensive applications.

Last month Snowflake announced the availability of Snowflake Data Clean Rooms, a service for securely sharing data in a way that preserves data privacy. (The new service is based on Snowflake’s acquisition of Samooha, a data clean room tech developer, in December 2023.

On Feb. 28 Snowflake announced that CEO Frank Slootman, who joined the company in 2019 and took it public in 2020, was retiring. Sridhar Ramaswamy, previously senior VP of Ads & Commerce at Google and co-founder of Neeva, which Snowflake previously acquired, was named Snowflake’s new CEO. That same day Snowflake said that revenue in its fiscal 2024 (ended Jan. 31) grew 36 percent year over year to just over $2.8 billion.