Base
Hardened build
minimal ports, security patches applied at build time
seekdb
Azure
Databases
1 variation
seekdb, a single node AI native database that unifies MySQL compatible SQL with built in vector and full text search in one engine.
Variations
This product is available in the build below. Open it for the operating system, cloud and version detail, or read its deployment guide.
| Product | Cloud | Operating system | Version | |
|---|---|---|---|---|
| seekdb on Ubuntu 24.04 LTS | Azure | Ubuntu 24.04 | Standard | View · Guide |
Overview
seekdb is an open source, single node database from the OceanBase project, built for applications and AI agents that need to store ordinary business data and semantic data side by side. It speaks the MySQL wire protocol, so existing MySQL clients, drivers and ORMs connect to it unchanged and standard SQL works as expected, while the same engine also stores dense and sparse vectors, builds HNSW indexes over them and answers approximate nearest neighbour queries. Because relational rows, full text and vectors live in one engine, a single SQL statement can filter on structured columns and rank by vector similarity together, which removes the usual pattern of running a separate vector index alongside a primary database and keeping the two in sync.
It is the single node member of the OceanBase family, aimed at one machine rather than a distributed cluster, so it stays a straightforward database to run while keeping the vector and hybrid search capabilities.
Why the cloudimg image
The cloudimg image installs seekdb from the vendor's own Ubuntu 24.04 package, checksum verified against the digest published on the upstream release. It generates a unique database root password on first boot, so no two customers share a login and no credential ships inside the image, and it refuses to finish booting if any account still accepts an empty password. The database and its management agent are restricted to loopback by default, with the guide showing exactly how to open the port to your own subnet when you want to. A dedicated data volume keeps the database, its redo log and its logs off the OS disk, log rotation is configured so the volume cannot fill, vendor telemetry is switched off, and the image is sized for the machine it boots on rather than the machine it was built on. Paired with a tested deployment guide and 24/7 support.
Common uses
- Semantic and hybrid search over your own documents
- Vector storage and retrieval for AI agents and RAG applications
- A MySQL compatible database for applications that also need similarity search
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