The Coolest Database System Companies Of The 2025 Big Data 100
Part 2 of CRN’s Big Data 100 takes a look at the vendors solution providers should know in the database systems space.
Running The Bases
More than 400 million terabytes of digital data are generated every day, according to market researcher Statista, including data created, captured, copied and consumed worldwide. By 2028 the total amount of global digital data is forecast to reach 394 zettabytes, up from 149 zettabytes in 2024.
Storing and managing all that data is a complex task. To make productive use of the ever-growing volumes of data, businesses and organizations need the right database systems to manage all that data and make it available for operational, analytical—and now artificial intelligence—purposes.
Not surprisingly, the global market for database management systems, which reached $151.6 billion in 2024, is forecast to grow at a compound annual growth rate of 14.5 percent to $344.4 billion by 2030, according to Research and Markets.
As part of the CRN 2025 Big Data 100, we’ve put together the following list of database system companies—from well-established vendors to those in startup mode—that solution providers should be familiar with.
These vendors offer next-generation relational database systems that can handle growing volumes of data and transactions, analytical databases designed to process complex queries against huge data sets—and some databases that can do both—along with more specialized systems such as graph databases and time series databases.
Given the wave of AI development that’s boosting the demand for data, many database vendors are adding new capabilities such as vector search to their systems to improve their performance for AI and generative tasks. Some newer databases are primarily designed for AI.
This week CRN is running the 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.
Aerospike
Top Executive: Subbu Iyer, CEO
Aerospike offers a high-performance, real-time, massively scalable NoSQL database designed for mission-critical applications that cannot experience downtime and require fast read and write throughput.
In February the company delivered Aerospike 8 with distributed ACID transaction capabilities to support large-scale OLTP (online transaction processing) applications and guarantee strict serializability of ACID transactions.
Before that, in December, Aerospike improved the database’s vector search capabilities with new indexing and storage innovations—a critical need for generative AI and machine learning applications.
In April 2024 Aerospike, based in Mountain View, Calif., raised $109 million in new funding to accelerate its development efforts.
ClickHouse
Top Executive: Aaron Katz, CEO
ClickHouse markets a high-performance, column-oriented SQL database for OLAP (online analytical processing) tasks, available as both open-source software and through the ClickHouse Cloud service. The use cases include data warehouse, real-time analytics, and machine learning and generative AI applications.
ClickHouse, founded in 2021 and based in Redwood City, Calif., also targets its database for observability tasks. That got a boost in March when the company acquired HyperDX, an open-source observability system built on top of the ClickHouse database.
Cockroach Labs
Top Executive: Spencer Kimball
Cockroach Labs, which just celebrated the 10th anniversary of its founding, markets its CockroachDB cloud-native, distributed SQL database for mission-critical transactional applications that require high availability and scalability.
In October Cockroach Labs formed a strategic collaboration agreement with Amazon Web Services that included “substantial investments” in driving integrated go-to-market activities across sales, marketing, technology integrations and commercial programs.
This month the New York-based company said it has recorded a 200 percent year-over-year increase in new customers and 80 percent year-over-year growth in new annual recurring revenue, and 100 percent year-over-year growth in the cloud.
Couchbase
Top Executive: Matt Cain, President, CEO
Couchbase offers its popular Capella cloud database—and the Couchbase NoSQL database server that Capella is based on—for developing mission-critical transaction, analysis, mobile and AI applications.
The company recently unveiled Capella AI Services to accelerate agentic AI application development. In February it revealed that its Capella AI Model Services had integrated Nvidia NIM microservices to streamline the deployment of AI-powered applications. And in March it debuted Couchbase Edge Server, an offline-first, lightweight database server for applications in edge environments.
EDB
Top Executive: Kevin Dallas, CEO
EDB has been expanding beyond its roots of selling a transaction-oriented, Oracle-compatible database based on open-source PostgreSQL. In 2024 the company debuted EDB Postgres AI, a database that can tackle transactional, analytical and AI application workloads. The new database offers rapid analysis for transactional data, intelligent observability, continuous high availability and support for vector databases.
In February EDB expanded its channel program, including increasing investments to raise partners’ expertise and go-to-market capabilities, as the company looks to boost adoption of its Postgres-based database platform for more data analytics and AI applications. The company also launched a new partner portal and “industry success hub” repository of vertical industry customer case studies that partners can draw on.
Exasol
Top Executive: Joerg Tewes, CEO
Exasol, based in Nuremberg, Germany, develops an in-memory, column-oriented database that serves as a high-powered analytics engine for turning massive volumes of data into actionable insight.
The database software is used to power next-generation data warehouses and to integrate AI and machine learning workloads into an organization’s analytics environment.
Fluree
Top Executive: Brian Platz, CEO
Fluree offers Fluree Core, a semantic graph database that guarantees data integrity and secure data sharing. The database system’s semantic graph architecture provides connected data insight while its immutable ledger technology is designed for trusted data collaboration and verifiable systems of record applications.
In addition to the main database, Fluree, based in Winston-Salem, N.C., offers Fluree Sense for cleaning and integrating data using AI and machine learning, and Fluree Content Auto-Tagging Manager for transforming unstructured data.
Imply Data
Top Executive: Fangjin Yang, CEO
Imply develops a real-time data analytics platform based on the open-source Apache Druid real-time database. The Burlingame, Calif.-based company was founded in 2015 by Druid’s original developers.
In 2024 the company launched Imply Polaris, a fully managed Database as a Service based on Apache Druid and running on the Microsoft Azure cloud platform.
InfluxData
Top Executive: Evan Kaplan, CEO
InfluxData develops the InfluxDB time-series database for real-time applications that collects, stores and analyzes time-series data at scale, allowing developers to query and analyze time-stamped data.
On April 15 InfluxData, a remote-first company, announced the general availability of the open-source InfluxDB 3 Core data engine and the commercial InfluxDB 3 Enterprise with additional high-availability, security and scalability capabilities for production environments. Additions to the new release, including a built-in Python processing engine, simplify how developers build applications with time series data.
Kinetica
Top Executive: Nima Negahban, CEO
Kinetica develops a high-performance, GPU-accelerated database for a range of complex analytical tasks including real-time and graph analytics, spatial intelligence and generative AI applications.
The Kinetica database offers real-time vector search and a built-in large language model—key capabilities needed by artificial intelligence and GenAI applications.
MariaDB plc
Top Executive: Rohit de Souza, CEO
MariaDB plc provides a commercial version of the popular MariaDB open-source relational database. The MariaDB database, a fork of the MySQL open-source database, was launched in 2010 by some of MySQL’s original creators after Oracle acquired MySQL as part of its acquisition of Sun Microsystems.
In January the company announced the general availability of MariaDB Enterprise Platform 2025 with new vector search capabilities for AI application development.
MongoDB
Top Executive: Dev Ittycheria, President, CEO
MongoDB has seen demand for its NoSQL, document-oriented database, including the MongoDB Atlas cloud database and development platform, surge to meet the needs of AI applications for huge volumes of unstructured data.
In May 2024 MongoDB made a big move in the AI space with the launch of the MongoDB AI Applications Program, a complete technology stack, services and other resources for developing and deploying advanced generative AI applications.
In February MongoDB acquired Voyage AI, a developer of “embedding and rerank” AI models that improve the accuracy and efficiency of RAG (retrieval-augmented generation) data search and retrieval operations.
Neo4j
Top Executive: Emil Eifrem, CEO
Neo4j is a leading provider of graph database software, a category of database systems that store and manage data in a way that emphasizes the relationships between data entities.
Graph databases make it easier to analyze interconnected data and identify patterns—a key benefit for such tasks as fraud detection, identity resolution and supply chain management.
Graph database technology, working with vector search and data science, can improve GenAI applications with more accurate responses and deep explainability of analytical results, according to Neo4j.
Pinecone
Top Executive: Edo Liberty, CEO
AI applications and large language models need fast access to data. That’s fueling the demand for vector databases that index and store “vector embeddings” for rapid data retrieval and similarity searches.
Pinecone’s distributed vector database, which the company describes as “the foundation for knowledgeable AI,” is used to build AI applications that are accurate, high-performance and scalable.
The San Mateo, Calif.-based company launched its Pinecone Partner Program in April 2024 with a focus on ISVs that build the company’s vector database into their software products, including AI applications.
Redis
Top Executive: Rowan Trollope, CEO
The Redis real-time, in-memory database, including the company’s enterprise database software and cloud database service offerings, is targeted toward developers building high-performance applications.
The Mountain View, Calif.-based company’s Redis for AI offering is an integrated package of database features and services for building and deploying GenAI applications, including chatbots and agents, that leverage the Redis database’s vector capabilities, integrations and scalability.
ScyllaDB
Top Executive: Dor Laor, CEO
ScyllaDB’s high-performance, distributed, NoSQL database platform is designed to handle millions of operations per second with high availability and linear scalability. The company’s product portfolio includes ScyllaDB Enterprise software and the ScyllaDB Cloud fully managed database service.
ScyllaDB, based in Sunnyvale, Calif., debuted ScyllaDB 2024.2 in December featuring the new “tablets” replication architecture that the company said boosts the database’s elasticity and efficiency.
SingleStore
Top Executive: Raj Verma, CEO
SingleStore’s distributed SQL database performs a range of tasks, including transaction processing, search and query processing/analysis—all on a unified database platform. The company touts the database’s fast data ingestion and built-in vector search capabilities as key for building and running AI applications.
The SingleStore database stores multiple types of data including relational, JSON, geospatial, key-value vector and time series data.
In October SingleStore, based in San Francisco, acquired BryteFlow, an Australian developer of data integration technology, in a move to expand the capacity of the SingleStore database to ingest data from ERP and CRM sources including SAP, Oracle and Salesforce.
In February the company launched SingleStore Flow, a no-code tool to simplify data migration and change data capture.
Tessell
Top Executive: Bala Kuchibhotla, CEO
Startup Tessell touts its Database-as-a-Service technology as a co-pilot for cloud databases, helping resolve issues of data fragmentation and inefficiency that often come with multi-cloud computing environments.
Tessell’s DBaaS platform provides a suite of database services, including data protection, security and compliance, and simplified management, that surround six other commercial database engines (Microsoft SQL Server, Milvus, MongoDB, MySQL, Oracle Database and PostgreSQL).
Earlier this month Tessell, based in San Francisco, raised $60 million in a Series B funding round, financing the startup will use to accelerate its go-to-market expansion and boost its research and development in AI-powered data management.
TigerGraph
Top Executive: Rajeev Shrivastava, CEO
TigerGraph’s hybrid transactional/analytical graph database can scale to handle hundreds of terabytes of data and is targeted toward data-intensive tasks such as customer data analysis, fraud detection, and AI and machine learning applications.
In January TigerGraph, based in Redwood City, Calif., debuted Savanna, a new evolution of its graph database with “native parallel graph” design that focuses on both storage and computation. TigerGraph said Savanna can rapidly process large volumes of connected data for AI and analytics applications.
Yugabyte
Top Executives: Co-CEOs Karthik Ranganathan, Kannan Muthukkaruppan
YugabyteDB is a high-performance, PostgreSQL-compatible, distributed database designed for mission-critical, transactional applications such as large-scale payment, order management and telematics systems. The company’s offerings include the YugabyteDB Aeon Database as a Service.
In January Yugabyte, based in Sunnyvale, Calif., unveiled a tech preview of YugabyteDB 2.25 with PostgreSQL 15 compatibility and a number of new features including generated columns and multirange aggregates for enhanced data modeling and querying.
This month Yugabyte launched Performance Advisor, the first of a line of agentic AI applications for YugabyteDB Aeon.
