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RAG Frameworks · oceanbase

seekdb

SeekDB is an AI-native embedded or server database designed for agent applications. It unifies vector search, full-text search, structured, and semi-structured data in a single engine with a MySQL-compatible SQL interface and ACID guarantees.

Source: GitHub — github.com/oceanbase/seekdb
2.8k
GitHub stars
261
Forks
C++
Primary language
Apache-2.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
Repositoryoceanbase/seekdb
Owneroceanbase
Primary languageC++
LicenseApache-2.0 — OSI-approved
Stars2.8k
Forks261
Open issues333
Latest releasev1.3.0 (2026-05-25)
Last updated2026-07-08
Sourcehttps://github.com/oceanbase/seekdb

What seekdb is

Built in C++ on the OceanBase SQL kernel, SeekDB features async index pipelines (Change Stream) that decouple writes from indexing, two-level HNSW for incremental vector search, and copy-on-write sandboxing (FORK/MERGE). Runs embedded in-process or as a server; compatible with LangChain, LlamaIndex, and Dify.

Quickstart

Get the seekdb source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/oceanbase/seekdb.gitcd seekdb# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Agent Memory and State Management

Continuous write + millisecond-later retrieval workloads. Async indexing keeps P99 flat under sustained concurrency; COW sandboxes allow agents to explore safely with FORK/MERGE rollback.

Hybrid Vector + Full-Text + Metadata Search

Single SQL query combining vector distance, MATCH clauses, and scalar filters without client-side N+1 merging. Useful for RAG systems requiring simultaneous semantic and keyword matching.

Embedded AI Applications

No external infrastructure; runs in-process via Python SDK or as a single-node server. MySQL protocol and ACID make it suitable for AI/ML apps needing real-time writes and queries without operational overhead.

Implementation considerations

  • Async indexing introduces a small lag between write commit and vector searchability; verify millisecond jitter tolerance for your agent loop timing.
  • FORK/MERGE COW sandboxes are powerful but require careful SQL design; ensure rollback/conflict strategies (FAIL/THEIRS/OURS) align with agent semantics.
  • Hybrid queries (vector + full-text + filter) must be carefully tuned; push filters into WHERE clauses to avoid full-table scans.
  • Embedded mode runs in-process (no separate server); single-process resource limits may constrain very large agent fleets.
  • Python SDK is the recommended integration path; native drivers or REST API coverage unknown.

When to avoid it — and what to weigh

  • Distributed cluster deployments — SeekDB documentation does not clearly state distributed cluster support. Single-node server or embedded mode only; scale-out architecture unknown.
  • Strict real-time consistency across nodes — Async Change Stream pipeline means indexing may lag writes slightly. Use cases requiring immediate global consistency should verify write-to-index latency SLAs.
  • Ultra-high throughput with complex joins — Benchmarks focus on streaming write + vector search; complex multi-table join performance is not documented. May not be optimal for traditional OLTP workloads.
  • Mature production at massive scale — SeekDB is relatively young (created Oct 2025, latest release May 2026). Early adoption carries risk; no clear customer case studies or long-term production telemetry provided.

License & commercial use

Apache License 2.0 (Apache-2.0). Permissive OSI license allowing use, modification, and distribution under Apache terms. Commercial use is permitted under the Apache-2.0 license without additional restrictions, subject to Apache license compliance (attribution, license text, statement of changes).

Apache-2.0 permits commercial use. However, SeekDB is a young open-source project (< 1 year old) with 2,794 GitHub stars and moderate community activity. No SLA, commercial support, or warranty is mentioned in the data provided. Commercial users should confirm: (1) whether OceanBase Ltd. or community provides paid support; (2) production-grade SLAs; (3) liability / indemnification terms. Evaluate risk tolerance for early-stage infrastructure dependencies.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationAdequate
License clarityClear
Deployment complexityLow
DEV.co fitStrong
Assessment confidenceMedium
Security considerations

No security audit, CVE history, or threat model is disclosed in the data provided. Considerations: (1) SeekDB is young; third-party security review status is unknown. (2) Embedded mode runs in-process; consider code provenance and supply chain risk. (3) Server mode exposes MySQL protocol; standard database security practices (network isolation, authentication, TLS) should be applied. (4) No mention of encryption at rest, key management, or compliance certifications (HIPAA, SOC 2, etc.). (5) Apache-2.0 license includes no security warranty. For regulated workloads (healthcare, finance, PII), perform your own security assessment or wait for community audit reports.

Alternatives to consider

Milvus

Pure vector database with mature ecosystem; SeekDB benchmarks claim 10.7× QPS advantage for streaming write + search, but Milvus has longer production track record and broader industry adoption.

Weaviate

Vector + metadata search with GraphQL API; more mature than SeekDB (longer development history) but less integrated with SQL and agent frameworks. No COW sandbox feature.

Elasticsearch + custom vector index

Software development agency

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seekdb FAQ

Is SeekDB production-ready?
SeekDB is actively maintained (latest release May 2026) and has decent GitHub adoption (2,794 stars). However, it is a young project (< 1 year old) with no disclosed large-scale production deployments or third-party audits. Use with caution in mission-critical systems; consider it suitable for AI/ML prototypes and early-stage agent deployments. Monitor community feedback and issue resolution.
Can I use SeekDB with LangChain or LlamaIndex?
SeekDB declares compatibility with LangChain, LlamaIndex, and Dify. The pyseekdb Python SDK is the recommended integration path. Verify adapter stability and version pins for your specific framework version before committing to production.
Does SeekDB require a separate server?
No. SeekDB runs embedded (in-process, via pyseekdb) or as a standalone single-node server. Docker and binary installers are provided. Distributed cluster support (if available) is not clearly documented; assume single-node for now.
How does the async index pipeline affect consistency?
Writes commit immediately and are queryable via full-table scan; vector indexing happens asynchronously in the Change Stream pipeline. This means newly written vectors may not appear in approximate (ANN) searches until the index pipeline catches up (lag is milliseconds). Plan your agent loop timing accordingly; read more in the technical docs.

Work with a software development agency

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