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DingoDB is an open-source distributed vector database that combines SQL (MySQL-compatible) with vector search capabilities to handle both structured and unstructured data at scale. It targets high-concurrency, low-latency workloads and is maintained by DataCanvas.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | dingodb/dingo |
| Owner | dingodb |
| Primary language | Java |
| License | Apache-2.0 — OSI-approved |
| Stars | 1.7k |
| Forks | 264 |
| Open issues | 8 |
| Latest release | v0.9.0 (2024-06-14) |
| Last updated | 2026-05-25 |
| Source | https://github.com/dingodb/dingo |
What dingo is
Java-based multi-modal vector database with Raft-backed strong consistency, hybrid scalar-vector indexing, automatic data sharding, cold-hot tiered retrieval, and MySQL protocol compatibility. Supports SQL, SDK, and API access modes with built-in high availability and elastic scaling.
Get the dingo source
Clone the repository and explore it locally.
git clone https://github.com/dingodb/dingo.gitcd dingo# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- JVM deployment and tuning required; use YourKit or equivalent profiling for performance-critical applications.
- Automatic sharding and index optimization reduce operational burden, but cluster sizing and partition strategy design are necessary.
- MySQL protocol compatibility enables familiar tooling but may mask behavioral differences; test application query patterns thoroughly.
- Raft-based storage (Dingo-Store) requires quorum availability; plan for odd-numbered node counts and network resilience.
- Real-time indexing is automatic, but hybrid scalar-vector query optimization rules are not detailed; benchmark for your query mix.
When to avoid it — and what to weigh
- Production systems requiring battle-tested stability — Latest release (v0.9.0) is still pre-1.0; adoption and production track record are not clearly documented. Requires careful evaluation for mission-critical deployments.
- Single-language, Python-first teams — Core is Java-based. While SDKs exist, Java expertise and JVM operational knowledge are beneficial.
- Minimal operational overhead desired — Distributed systems require coordination infrastructure (Raft-based), cluster planning, and operational maturity—not a drop-in single-node solution for most use cases.
- Vendor-backed SaaS with guaranteed uptime SLA — Open-source with no clearly stated commercial support offerings or enterprise SLAs in the provided data.
License & commercial use
Apache License 2.0 (OSI-approved permissive open-source license). Allows commercial use, modification, and distribution with minimal restrictions; includes liability disclaimer.
Apache-2.0 permits commercial use without license fees. However, no data on commercial support, indemnification, or enterprise SLAs; a commercial arrangement with DataCanvas (sponsor) may be available but is not documented in provided materials. Requires review for risk-averse deployments.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | High |
| DEV.co fit | Good |
| Assessment confidence | Medium |
No security audit, threat model, or vulnerability disclosure process mentioned in provided data. Raft-based consensus provides integrity guarantees against single-node compromise. MySQL protocol compatibility inherits SQL injection risks; validate prepared statement support and input sanitization. Network segmentation and authentication mechanisms not detailed; requires security review before production use.
Alternatives to consider
Weaviate
Open-source vector DB with REST/GraphQL APIs and hybrid search; mature project with commercial support. Java-based like DingoDB but distinct ecosystem.
Milvus
Open-source vector database with similar scaling and consistency guarantees. C++ core; more established adoption track record.
Pinecone
Managed SaaS vector database with strong consistency and low-latency guarantees. Eliminates operational overhead but requires vendor commitment.
Build on dingo with DEV.co software developers
DingoDB offers a compelling open-source alternative for hybrid scalar-vector workloads with strong consistency. Contact us to assess fit for your architecture, benchmark performance, and plan a proof-of-concept deployment.
Talk to DEV.coRelated on DEV.co
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dingo FAQ
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Can I use DingoDB as a drop-in MySQL replacement?
What are the operational requirements?
Does DingoDB offer commercial support?
Senior engineers for your next build
Our engineers ship vector databases software for a living. DEV.co provides software development services, web development services, and ongoing support for teams standardizing on tools like dingo.
Evaluate DingoDB for Your Vector Search Needs
DingoDB offers a compelling open-source alternative for hybrid scalar-vector workloads with strong consistency. Contact us to assess fit for your architecture, benchmark performance, and plan a proof-of-concept deployment.