Ship faster with managed data infrastructure
Store, retrieve, and manage data across every stage of AI development and production, without managing the infrastructure yourself. Powered by PostgreSQL, the open-source database trusted by AI builders and ML engineers.
Address any use case with PostgreSQL
From low-latency vector search with pgvector to fast transactional reads and rich querying, PostgreSQL covers the full range of modern AI data needs, RAG pipelines, agent state, application backends, and ML metadata, all in one database.
A production-grade database in minutes
Access a fully managed PostgreSQL with no servers to configure, no backups to schedule, and no ongoing maintenance. Ready to connect from day one, without DevOps expertise required.
Built into your AI stack
Your database runs in the same cloud as your GPU clusters and inference endpoints. Data stays close to where it is consumed, with no cross-cloud overhead and no public internet round-trips between your models and your data.
Built for modern AI and ML workflows
RAG and vector search
Store document embeddings alongside your structured data using pgvector. Run semantic similarity searches directly in SQL, with no separate vector database required. Feed retrieval results into your inference pipeline with minimal latency.
AI agent state and memory
Give your agents reliable operational memory. Store conversation history, task status, tool call results, and session context in a transactional database that handles concurrent reads and writes without data loss.
AI application data
Back your LLM-powered product with a full relational database. Manage users, sessions, content, and configuration alongside your AI logic, in the same PostgreSQL instance with the query interface your team already knows.
ML data management
Track dataset versions, store metadata, manage experiment inputs, and record data lineage. PostgreSQL gives ML teams a structured, queryable record of the data that feeds model development, compatible with any MLOps tooling or custom tracking approach.
Low-latency retrieval for every inference request
Low-latency retrieval for every inference request
Managed Service for PostgreSQL runs alongside your GPU compute instances on Nebius, so every database call your inference stack makes, stays on the internal network. This lets you build production endpoints for AI applications and agents that serve requests with low end-user latency, all inside the same security domain.
Beyond PostgreSQL
Beyond PostgreSQL
DataOps on Nebius starts with Managed Service for PostgreSQL, but your choice of data tools does not stop there. Through Nebius Applications, you can deploy additional relational or vector databases, pipeline orchestrators, and data processing tools directly into your cloud environment, working seamlessly alongside your existing infrastructure.
Extend your AI pipeline with human intelligence
Extend your AI pipeline with human intelligence
For production AI applications and agents where output quality matters, Tendem by Toloka adds a verified human judgment layer to your pipeline. Connect your agents to a network of 10,000+ domain experts via MCP to validate outputs, resolve ambiguity, and handle edge cases that automation alone cannot cover.
Get started
Start benefiting from DataOps in the Nebius console at your own pace, or reach out to our team if you have questions about your data architecture or specific use case.
