Milvus vs MyScale
A side-by-side comparison of Milvus and MyScale, two Vector DB tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
MyScale
Vector DBSQL vector database built on ClickHouse — vector, full-text, and analytics in one query.
View MyScaleAt a glance
| Attribute | Milvus | MyScale |
|---|---|---|
| Category | Vector DB | Vector DB |
| Pricing | FREEMIUM | FREEMIUM |
| License | Open core | Open core |
| Deployment | Hybrid | Hybrid |
| Platforms | API | API |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | Zilliz | MyScale |
| Capabilities (differs) |
|
|
The honest brief
Milvus
Storage/compute split plus DiskANN make it the most robust open-source choice at billion-vector scale.
- Scales to billion-vector deployments
- Storage/compute separation
- Many index types (HNSW, IVF, DiskANN) + GPU
- Mature project with a large community
- Operationally heavy to self-host
- Overkill for small workloads
- Performance hinges on data quality
- Higher latency than Qdrant at p50
MyScale
Built as a ClickHouse fork, so one SQL query can mix vector search, full-text search, and analytics—no separate vector store to keep in sync.
- Open source (Apache-2.0), self-hostable
- SQL joins vectors with structured data
- Built on battle-tested ClickHouse
- Free managed starter pod
- Smaller community than Pinecone/Milvus
- Open-source release cadence slowed after 2024
- SQL-first model has a learning curve
When to pick which
Both cover Vector search, Unified search, and RAG pipeline.
Pick Milvus if you need Recommendation engine.
- Recommendation engine (secondary capability)
MyScale leans on Unified search as a headline capability; Milvus treats it as secondary.
- Unified search (primary capability)