CoreWeave Database Launches So AI Teams Can Build, Run, and Scale Production Applications on One Platform

Customers retain control of their data and database users while CoreWeave handles replication, failover, patching and backups.

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CoreWeave Database places a fully managed, PostgreSQL-compatible database inside CoreWeave Kubernetes Service clusters, removing the cross-cloud hop between AI applications and the data they depend on

LIVINGSTON, N.J.--(BUSINESS WIRE)-- CoreWeave, Inc. (Nasdaq: CRWV), The Essential Cloud for AI^®, today announced the general availability of CoreWeave Database, a managed PostgreSQL service that runs inside customers' CoreWeave Kubernetes Service (CKS) clusters, alongside their training and inference workloads. CoreWeave Database gives AI teams a production-ready relational database on the same platform as their GPUs, with high availability, continuous backups, and point-in-time recovery built-in.

Nearly every AI stack depends on a relational database for application state, workflow metadata, and experiment tracking. Until now, teams building on CoreWeave either operated PostgreSQL themselves or kept it in another cloud, adding a network hop, an egress path, and a second environment to secure. That distance grows as AI moves into production. Agents read and write state between tool calls, training jobs log experiment metadata, and retrieval-augmented generation (RAG) services query embeddings, all hitting the database on every step. When those calls cross clouds, latency and operational overhead compound. CoreWeave Database closes that distance.

"AI in production runs on more than GPUs. It runs on the application state, metadata, and embeddings that agents and training pipelines touch on every step," said Corey Sanders, SVP of product, CoreWeave. "CoreWeave Database puts that data in the same cluster as the compute that depends on it, operated by CoreWeave so teams can spend their time on models instead of database operations. It extends The Essential Cloud for AI to the full production stack."

CoreWeave Database is fully compatible with PostgreSQL, so teams can migrate existing databases from another cloud or a self-managed deployment using native Postgres tools. CoreWeave operates replication, failover, patching, and backups, while customers retain ownership of their data, schemas, queries, and database users. Key capabilities include:

• In-cluster placement: Databases run on CPU nodes in the customer's CKS cluster and connect through an in-cluster Kubernetes service, with no cross-cloud link or egress path to manage.
• High availability: Each database runs a primary instance and reads replicas spread across hosts, with automatic failover, and stores live data on CoreWeave Distributed File Storage (DFS).
• Built-in data protection: Every database is continuously backed up by default, with point-in-time recovery to any moment within the retention window, scheduled and on-demand backups, and full restores to a new cluster for validation.
• Private and encrypted by default: Databases stay private to the cluster. Data is encrypted at rest and in transit, CoreWeave manages TLS certificates and security patches, and customers control access through native PostgreSQL roles, Kubernetes network policies, and audit logging.
• Vector search for AI workloads: CoreWeave Database supports pgvector, so teams can store embeddings and run vector search for RAG and semantic retrieval in the same database as their application data, with no separate vector store to run.

“Migrating our biomedical literature database from another cloud to CoreWeave Database was straightforward, and the CoreWeave team helped us get to production quickly,” said Mike Mattacola, CEO, Advaita Bio. “We’ve really appreciated their hands-on support every step of the way. Our managed PostgreSQL now runs alongside the applications that depend on it, and we’re confident our data is encrypted, private, and backed up.”

CoreWeave Database leverages CloudNativePG (CNPG), the open-source Kubernetes operator for PostgreSQL, which handles primary and replica management and failover. CoreWeave adds the managed service around it, including Console and Kubernetes workflows, DFS, managed backups, monitoring, and ongoing operations. CoreWeave also contributes upstream to the PostgreSQL ecosystem, with recent work including S3 compatibility improvements in Barman, the open-source backup and recovery tool, and connection configuration improvements in pgexporter, a Prometheus exporter for PostgreSQL metrics. The launch extends CoreWeave's platform beyond compute into the services production AI applications depend on, building on its standing as the only AI cloud to earn the top Platinum ranking in SemiAnalysis ClusterMAX™ three times in a row.

CoreWeave Database is generally available today. Click here to get started.

About CoreWeave

CoreWeave is The Essential Cloud for AI^®. Built for pioneers by pioneers, CoreWeave delivers a fully integrated platform of technology and teams that enables innovators to move at the pace of innovation, building and scaling AI with confidence. Trusted by 9 of the 10 leading foundation model providers, CoreWeave serves as a force multiplier by combining superior infrastructure performance with deep technical expertise to accelerate human discovery. Established in 2017, CoreWeave completed its public listing on Nasdaq (CRWV) in March 2025.

View source version on businesswire.com: https://www.businesswire.com/news/home/20261111687728/en/

press@coreweave.com

Source: CoreWeave, Inc.

Key Terms

postgresql technical

PostgreSQL is a widely used open-source database system that stores, organizes and retrieves structured data for applications, like a digital filing cabinet with a smart librarian that finds and updates records quickly. For investors, it matters because the choice and performance of a database affect a company’s product reliability, scaling capacity, operating costs and security posture, which in turn influence revenue potential and risk.

point-in-time recovery technical

Point-in-time recovery is the amount of money a lender, investor, or insurer expects to get back from a distressed or defaulted asset measured at a specific moment, rather than averaged over many economic cycles. It matters because it gives a current snapshot of loss mitigation—like checking a bank account balance right after a sale—helping investors estimate immediate recoveries, set reserves, and price risk based on present conditions rather than long-term averages.

retrieval-augmented generation technical

An AI method that combines a conversational language system with live access to external documents or databases, so the AI first fetches relevant facts and then uses them to form its answer. Think of it as an assistant that checks a file cabinet for source papers before replying, which helps reduce mistakes and reveal evidence. For investors it matters because it can produce more accurate, verifiable summaries of filings, news and research, speeding due diligence while still depending on the quality of the underlying data.