RedDB Cloud · Source available
Stop running 7 databases. Run RedDB.
Postgres, Mongo, Redis, Pinecone, Neo4j, Influx, RabbitMQ — replaced by one engine that also answers natural-language questions across your data. For startups that can't afford a 5-person infra team.
Or self-host with npm i @reddb/cli
- 7→1
- databases consolidated
- <1ms
- cache-hit latency
- fsync+WAL
- durable on every commit
- BSL 1.1
- every line auditable
The stack problem
Your app should not need seven databases to answer one question.
Most startups end up paying five vendors and writing the glue between them. RedDB makes the data model a query capability instead of a separate product to deploy, sync, observe and recover.
Fragmented stack
- Postgres
- rows
- Mongo
- docs
- Neo4j
- graphs
- Pinecone
- vectors
- Redis
- kv + cache
- Influx
- metrics
- RabbitMQ
- queues
RedDB
- Collections
- one engine
- ASK
- cross-model context
- Drivers
- Rust · JS · Python
One engine. Everything on top.
The database is the start. AI runs on it.
Retrieval, embeddings and grounded answers already ship inside the engine. On top of it we are building the services your models and agents need — memory, storage, a model API and a place for agents to live.
Live in the engine today
Ask your data. Get the receipts.
ASK pulls context from rows, documents, graph edges and vectors, then answers with citations tied to the records it used. Embeddings happen on write; similarity search is a query, not another service.
- Embeddings on write. An EMBED policy on a collection embeds the declared fields asynchronously over CDC, so writes never wait on the provider.
- Vector and hybrid search. SEARCH SIMILAR, hybrid text + vector search, and HNSW indexes that apply filters before ranking.
- MCP for agents. Agents read and write durable state in RedDB through the Model Context Protocol, over stdio.
ASK 'who owns passport AB1234567 and what do they use?' USING groq;Answer
Alice Costa owns passport AB12345671 and uses billing, admin-console and vpn2. A suspicious login was flagged on her account3.
| Ref | Collection | Kind | Record used |
|---|---|---|---|
| [1] | users | table row | passport AB1234567 → Alice Costa |
| [2] | identity | graph edge | OWNS → billing, admin-console, vpn |
| [3] | logs | document | warning: suspicious login |
Built on the engine · planned
Everything your agents need, on the same data.
These managed services are on the way. Tell us what you would run on them — we onboard early users by email and talk fit before anything is deployed.
- Agent Hosting Planned
A home for the agents you choose.
Planned managed hosting for Hermes Agent, OpenClaw and Paperclip, with persistent customer environments.
- Agent Memory Planned
Give the next session somewhere to start.
Extracted on write, embedded, and recalled by meaning when the next session starts.
Explore by product
Start with the database. Build on it.
Every product line shares one engine. The database is live today; around it we ship AI features in the engine and build the services and agents that use it.
- /p/dbaas Live
Database
One engine for tables, documents, graphs, vectors, KV, cache, time-series and queues — with natural-language ASK across all of it. Managed Cloud or self-host under BSL 1.1.
- /p/ai Live + planned
AI
ASK, embeddings, vector search and MCP ship in the engine today. Models, agent memory, artifact storage and agent hosting are planned.
60 seconds to first query
Merge the stack. Ship the next thing.
Claim a free nano database on Cloud — no credit card, no sales call — or self-host it free under BSL 1.1.
npx reddb-cli@latest server --http --bind 127.0.0.1:5055
docker run --rm -p 5055:5055 ghcr.io/reddb-io/reddb:latest