dingo
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
Is DingoDB suitable for a production system today?
Can I use DingoDB as a drop-in MySQL replacement?
What are the operational requirements?
Does DingoDB offer commercial support?
Software developers & web developers for hire
From first prototype to production, DEV.co delivers software development services around tools like dingo. Our software development agency staffs experienced software developers and web developers for custom software development, web development, integrations, and ongoing support across vector databases and beyond.
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.