Part 6 of CRN’s Big Data 100 takes a look at the vendors solution providers should know in the database systems space.
It’s estimated that 173 zettabytes of digital data were created in 2025—that’s nearly half a zettabyte or about 474 million terabytes every day, according to the DesignRush website. That number is expected to more than triple by 2029 to 527 zettabytes per year or about 1.44 zettabytes every day.
Managing all that data is a complex task. So is making productive use of the ever-growing volumes of data for operational, analytical and—more recently—artificial intelligence applications.
That’s why database systems are such a critical component of the big data ecosystem. The global database software market is estimated to have reached $186.1 billion in 2025 and is forecast to grow at a CAGR of 9.7 percent to $295.7 billion in 2030, according to The Business Research Company.
As part of the CRN 2026 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 2026 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. While Microsoft and Oracle are major players in the database space, for example, they appeared in the Big Data 100 Systems and Platforms slide show.
Aerospike
Top Executive: Subbu Iyer, CEO
Aerospike’s high-performance, real-time NoSQL database is designed to handle huge volumes of data as it processes transactions in milliseconds and performs millions of operations per second.
The technology, purpose-built to prevent system downtime, is most widely used for such use cases as payment processing and finance, fraud detection, e-commerce services and recommendation engines, and online bidding and ad impressions.
The company added real-time distributed ACID transaction capabilities to the database with last year’s launch of the current Aerospike Database 8 release. The company also offers a fully managed database-as-a-service, the Aerospike Graph database, and Aerospike Voyager for visualizing data and testing queries.
More recently, Aerospike has been positioning itself as a real-time database for AI, providing a high-performance data engine to support large language models and AI applications and agents in production. The database’s patented Hybrid Memory Architecture and ability to handle key-value, document and vector data workloads make it more effective for AI tasks than other databases and data warehouse systems, according to the company.
ClickHouse
Top Executive: Aaron Katz, CEO
ClickHouse, a relative newcomer (founded in 2021), markets a fully managed cloud database service based on technology that began as an internal project at Yandex in 2009 and released as an open-source database in 2016.
The database itself is a columnar SQL database designed for real-time OLAP (online analytical processing) tasks that’s capable of querying and analyzing massive datasets in milliseconds. Target use cases include real-time reporting dashboards and user-facing analytics, high-performance data warehousing, and analyzing large volumes of telemetry data.
For AI tasks the system can process data streams for machine learning models and conduct fast vector searches for generative AI applications.
In late May ClickHouse said its annual revenue run rate had surpassed $250 million and the company had 4,000 customers—including 1,000 added just since January. The fast-growing company also launched its inaugural partner program in May.
In January the company raised $400 million in Series D financing.
Cockroach Labs
Top Executive: Spencer Kimball, Co-Founder and CEO
Cockroach Labs develops CockroachDB, a cloud-native, distributed SQL database for developing and running mission-critical transactional applications that require high availability, resilience and scalability.
CockroachDB Enterprise is the flagship of the company’s product portfolio, which also includes the fully managed CockroachDB Cloud, CockroachDB Bring Your Own Cloud and CockroachDB for Agents.
Cockroach Labs has been expanding CockroachDB’s functionality with distributed vector indexing, hybrid search and querying, and other capabilities to support AI and machine learning workloads. In the AI space the company’s emphasis is on supporting autonomous agentic AI systems that run continuous, high-concurrency tasks.
In May Cockroach Labs announced that CockroachDB runs on IBM mainframe systems, supporting the IBM s390x processor architecture and making it possible to deploy CockroachDB on IBM Z systems running Linux and IBM LinuxONE.
Couchbase
Top Executive: BJ Schaknowski, CEO
Couchbase’s distributed NoSQL database platform is designed for high-performance enterprise applications that require massive scalability and sub-second latency.
The database’s capabilities include multi-model support, SQL++ querying, high availability, AI and vector search, a JSON-native document store, and support for mobile and edge systems.
In addition to the foundational Couchbase Server database, the company offers the popular Couchbase Capella, a fully managed database-as-a-service, and an embedded edition for mobile devices.
In December Couchbase announced the general availability of Couchbase AI Services, a comprehensive suite of new capabilities that bring together operational data, vector processing and AI models on a single platform and enable businesses and organizations to build, deploy and govern agentic AI applications.
EDB
Top Executive: Kevin Dallas, CEO
For many years EDB, previously known as EnterpriseDB, was focused on selling a transaction-oriented, Oracle-compatible database based on the open-source PostgreSQL database. But the company pivoted in 2024 and debuted EDB Postgres AI, a Postgres database that can tackle mission-critical transactional, analytical and AI application workloads across sovereign, hybrid environments.
In May EDB launched EDB Postgres Distributed 6.4, the distributed transactional foundation of EDB Postgres AI, with new capabilities that the company said deliver “the durability guarantees and architectural simplicity” required by top-tier financial and infrastructure applications.
EDB is a leader in the Postgres community and is a major technology contributor to the open-source Postgres platform.
Exasol
Top Executive: Joerg Tewes, CEO
Exasol develops a high-performance, in-memory relational database, the Exasol Analytics Engine, that’s specifically designed for data analytics, data warehousing and AI/machine learning chores.
The database is built on a distributed, shared-nothing, massively parallel processing (MPP) architecture.
In January, Exasol launched Exasol Personal, a free edition of the analytics database designed for individual users including analysts, data scientists, developers and technical enthusiasts.
InfluxData
Top Executive: Evan Kaplan, CEO
InfluxData develops the InfluxDB time-series database for real-time applications that collect, store and analyze time-series data at scale, allowing developers to query and analyze time-stamped data.
In April, the company announced the general availability of InfluxDB 3 Core and InfluxDB 3 Enterprise, delivering significant performance gains and architectural flexibility compared to earlier editions, according to InfluxData. Core is an open-source “recent-data” engine for real-time applications while Enterprise builds on that foundation with new high-availability, enhanced security, automatic failover, and scalability features for production environments.
InfluxDB partners with AWS, which provides Amazon Timestream for InfluxDB, a managed offering for AWS customers to run open-source InfluxDB natively within the AWS Management Console. That allows developers to quickly build and run time-series applications on AWS managed infrastructure.
InterSystems
Top Executive: Phillip “Terry” Ragon, CEO, Founder and Owner
The InterSystems IRIS database is a high-performance, multi-model data platform for storing and accessing various data types including SQL relational tables, objects, hierarchical arrays and JSON documents. The database combines transactional processing and real-time analytics in a single system.
The InterSystems database is most frequently used in the healthcare and finance industries and by government agencies and the company offers vertical industry solutions built on the flagship database. InterSystems IRIS for Health, for example, is a healthcare data-specific database that runs such applications as HealthShare Unified Care Record and InterSystems Payer Services.
Kinetica
Top Executive: Nima Negahban, Co-Founder and CEO
The Kinetica Active Analytics Platform is a distributed, memory-first, online analytical processing (OLAP) database that’s designed to leverage Nvidia GPUs and modern vector processors to process complex queries across large volumes of real-time data.
The database’s capabilities span vector search, time series, graph, spatial and key value lookup computing. It’s most frequently used for such tasks as real-time fraud detection, location intelligence and tracking, IoT and sensor analysis, streaming anomaly detection, and processing live data for AI.
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.
The MariaDB plc company, headquartered in Milpitas, Calif., went through a couple of turbulent years following an unsuccessful attempt to go public in 2022. MariaDB plc was acquired in September 2024, by K1 Investment Management, a leading investor in small-cap software companies.
Rohit de Souza, appointed CEO after the K1 acquisition, has led a turnaround as the company looks to regain its stride. In October 2025 the company announced the availability of MariaDB Enterprise Platform 2026, which unifies transactional, analytical and AI vector database engines into a single, high-performance platform.
In August 2025, MariaDB plc bought SkySQL, a database-as-a-service provider. In March of this year the company acquired GridGain, a developer of in-memory data processing technology, to boost the performance of data infrastructure for AI agentic computing.
MongoDB
Top Executive: Chirantan “CJ” Desai, President and CEO
MongoDB is among the more prominent of the next-generation database developers with its popular NoSQL document database that integrates operational and vector database capabilities in a unified platform. MongoDB Atlas is the company’s fully managed database-as-a-service offering.
The company promotes its database as a superior platform for developing and deploying high-performance applications—including AI applications and agents.
In January MongoDB expanded the AI capabilities of its database and application development platform with the addition of the embedding and reranking model technology the company acquired in 2025 when it bought Voyage AI. The move, according to the company, improves the accuracy of AI applications as they move from development into production.
In November MongoDB hired former Cloudflare and ServiceNow executive Chirantan “CJ” Desai as the company’s new President and CEO, taking over from Dev Ittycheria who retired after serving 11 years in the CEO job.
For its fiscal 2026 (ended Jan. 31) MongoDB reported revenue of $2.46 billion, up nearly 23 percent from $2.01 billion one year earlier.
Neo4j
Top Executive: Emil Eifrem, CEO
Neo4j is a leading provider of graph database software, a category of database technology that stores and manages data in a way that emphasizes the relationships between data entities.
By modeling information as interconnected nodes, relationships and properties, the Neo4j database can perform complex queries and highly contextual analysis of interconnected data – a key benefit for such tasks as fraud detection, identity resolution and supply chain management.
In October 2025 Neo4j said it was investing $100 million to boost its position as the “default knowledge layer” for agentic systems and critical infrastructure for generative AI. The funding is being used for product development, two new agentic offerings, and the launch of a program to support AI native startups.
Pinecone
Top Executive: Edo Liberty, Founder and CEO
Because the Pinecone database acts as the long-term memory for large language models and autonomous agents, Pinecone has become something of a superstar as the wave of AI development sweeps through the IT industry.
The company’s fully managed vector database is specifically designed to store, index and query high-dimensional numerical data (vector embeddings) generated by AI models. The database powers retrieval-augmented generation (RAG), semantic search, and AI agents by enabling real-time, low-latency similarity searches across billions of records.
In May, Pinecone launched Nexus, a knowledge engine designed for AI agents. Earlier this month Pinecone said Nexus is now integrated with Microsoft OneLake, bringing AI agents directly to enterprise data.
Redis
Top Executive: Rowan Trollope, CEO
Redis is the sponsor and commercial provider of the popular open-source Redis database, in addition to developing other related products. With its sub-millisecond data latencies, the Redis real-time, in-memory, NoSQL database is geared toward developers building high-performance applications.
Products developed by Redis, the company, include Redis Iris, a real-time context and memory engine for AI agents. Other products include Redis Context Retriever, which helps agents navigate real-time data; Redis LangCache, which provides semantic caching for AI; Redis Agent Memory and Redis Data Integration.
In September 2025, Redis acquired Decodable and its real-time streaming data platform in a move to bolster its capabilities as a real-time context and memory engine for AI applications.
Rocket Software
Top Executive: Milan Shetti, President and CEO
Rocket Software is a provider of IT infrastructure modernization, data management and application development services and solutions. The company helps enterprises bridge legacy mainframe systems with modern, hybrid cloud environments.
Rocket makes this list because in May it closed its acquisition of Vertica, an enterprise-grade analytics database platform, from OpenText. Rocket said the acquisition advances its strategy to bring intelligence to its IT modernization services by combining trusted core systems with high-performance analytics and AI that help organizations unlock the full potential of their data.
Rocket said the Vertica database complements its DataEdge and ContentEdge offerings.
Vertica was originally developed by computer scientist Michael Stonebraker and has changed ownership multiple times including being owned by Hewlett Packard Co., Micro Focus and OpenText.
ScyllaDB
Top Executive: Dor Laor, Co-Founder and CEO
ScyllaDB’s high-performance, distributed, NoSQL database is designed to handle millions of operations per second with high availability and linear scalability. The database was originally created as an alternative to the open-source Apache Cassandra database, although the company said ScyllaDB has become popular as an alternative to the Amazon DynamoDB database.
ScyllaDB has been targeting its technology toward real-time AI uses cases that require high-throughput and low-latency performance.
The company’s product portfolio includes ScyllaDB Enterprise software, the ScyllaDB Cloud fully managed database-as-a-service, and ScyllaDB Vector Search.
In January the company announced the general availability of ScyllaDB X Cloud, an elastic database that can achieve predictable performance at scale without overprovisioning its capacity.
SingleStore
Top Executive: Raj Verma, CEO
The SingleStore Helios database-as-a-service is designed for data and AI applications that require extremely high performance and low latency. The database, according to the company, can process a trillion rows per second of data ingestion and query processing.
The database combines transaction processing (OLTP) and analytical processing (OLAP) capabilities in a single data engine that can handle petabyte-scale datasets for analytics, transactions and search tasks.
The company also offers SingleStore Aura, a serverless, elastic compute and AI platform that’s integrated directly into the SingleStore database that developers use to run containerized applications, machine learning models and generative AI features next to live data.
In September SingleStore announced a growth buyout agreement with Vector Capital Management under which the private equity firm acquired majority ownership of SingleStore. Financial terms were not disclosed. Long-term shareholders including Google Ventures, IBM, Dell Technologies Capital and REV Venture Partners remain as investors. CEO Raj Verma and the SingleStore management team continue to lead the business.
Tessell
Top Executive: Bala Kuchibhotla, Co-Founder and CEO
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 plague 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 other commercial database engines including Microsoft SQL Server, MongoDB, MySQL, Oracle Database and PostgreSQL.
In September 2025 Tessell launched Data Ecosystem pipelines for data lakes and data warehouses, a new capability the company said unifies operational and analytical data in near real time and stores it in Microsoft’s OneLake, the central storage layer for Microsoft Fabric.
TigerGraph
Top Executive: Rajeev Shrivastava, CEO
TigerGraph develops an AI-powered distributed graph database for real-time applications such as fraud detection, anti-money laundering, cybersecurity/threat detection, entity resolution, customer 360, product recommendations, and supply chain management.
The company’s database incorporates a native parallel graph design that focuses on both storage and compute, supporting real-time graph updates and providing built-in parallel computation.
TigerGraph Savanna is the company’s managed cloud graph database service.
Yugabyte
Top Executive: Karthik Ranganathan, Co-Founder and Co-CEO
Yugabyte is a rising star in the database arena with its highly scalable, distributed YugabyteDB database that’s targeted for mission-critical, cloud-native applications where data integrity and continuous available are key.
YugabyteDB features PostgreSQL compatibility, a familiar relational database interface, support for ACID transactions, and such capabilities as stored procedures, triggers and extensions.
Deployment options include YugabyteDB Aeon, a fully managed cloud database service; YugabyteDB Managed, a fully managed database-as-a-service available on public clouds; and YugabyteDB Anywhere, a self-managed, private database-as-a-service.
In May Yugabyte launched Meko, an agent-native data infrastructure for multi-agent AI systems and agentic applications that work and learn together. As enterprises deploy AI agents to automate complex workflows, the Meko technology is designed to provide AI agents with the persistent, shared memory and knowledge they need to compound their learning over time.
In April Yugabyte struck a Strategic Collaborative Agreement (SCA) with Amazon Web Services through which the two companies are accelerating their joint go-to-market efforts and technical collaboration.
