vs

Deep Lake vs Milvus

Deep Lake: Activeloop's tensor-native data engine for AI: vectors, multimodal data and versioning on object storage. Milvus: Cloud-native, distributed open-source vector database built for billions of vectors.

key differences

  • Milvus is built for larger datasets (Multi-PB) than Deep Lake (≤ 1 PB).
  • Transactions: Deep Lake offers limited ACID; Milvus offers none.
  • Only Deep Lake has columnar storage, time travel, branching.
  • Only Milvus has secondary indexes, change data capture, ttl / expiry, role-based access, online schema changes.
  • Deep Lake has a serverless option; Milvus does not.

choose deep-lake for

  • +Multimodal datasets shared by training and RAG
  • +Versioned computer-vision datasets
  • +Agent memory over documents and images

best at · Vector search, RAG, Lakehouse

choose milvus for

  • +Billion-scale semantic and image search
  • +RAG platforms serving many teams
  • +Recommendation and deduplication
  • +Multimodal retrieval over lakehouse data

best at · Vector search, RAG, Search

overview
Primary model
Vector
Vector
Also supports
Array / Scientific, Columnar / OLAP
Search Engine, Document
Type
Database engine
Database engine
Status
Active
Active
Developer
Activeloop
LF AI & Data Foundation (developed mainly by Zilliz)
First release
2019
2019
Latest version
4.7.4 (Aug 25, 2026)
3.0.4 (Oct 26, 2026)
License
Open source (permissive)Apache License 2.0
Open source (permissive)Apache License 2.0
Free tier
✓
✓
popularity
WhichDB Score
12.2
45.9
Rank
#273
#35
GitHub stars
9.3K
46.5K
Stack Overflow questions
–
208
scale & guarantees
Comfortable data size
Large (≤ 1 PB)
Massive (Multi-PB)
Horizontal scaling
Native
Native
Multi-region
None
None
ACID
Limited
None
Consistency
Eventual
Tunable, Strong, Eventual
Schema
Flexible
Strict
Architecture
Embedded, Serverless, Shared storage
Distributed, Shared storage, Embedded, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
✓
✓
Serverless
✓
—
Embedded
✓
✓
Edge
—
—
Clouds
AWS, Google Cloud, Azure
AWS, Google Cloud, Azure
capabilities
Transactions
—
—
Joins
—
—
Secondary indexes
—
✓
Full-text search
✓
✓
Vector search
✓
✓
Geospatial
—
—
JSON
✓
✓
Change data capture
—
✓
Triggers
—
—
Stored procedures
—
—
Materialized views
—
—
TTL / expiry
—
✓
Pub/Sub
—
—
Columnar storage
✓
—
In-memory
—
—
Durable persistence
✓
✓
Compression
✓
✓
Encryption at rest
—
—
Role-based access
—
✓
Time travel
✓
—
Branching
✓
—
Online schema changes
—
✓
Streaming ingest
—
✓
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
TQL (Tensor Query Language), SQL (Postgres interface)
Milvus API (boolean filter expressions)
Client languages
Python, JavaScript
Python, Java, Go, Node.js, C#, Rust
Best for
Vector search, RAG, Lakehouse, Feature store
Vector search, RAG, Search

Deep Lake vs Milvus: FAQ

What is the difference between Deep Lake and Milvus?

Deep Lake: Activeloop's tensor-native data engine for AI: vectors, multimodal data and versioning on object storage. Milvus: Cloud-native, distributed open-source vector database built for billions of vectors. Milvus is built for larger datasets (Multi-PB) than Deep Lake (≤ 1 PB). Transactions: Deep Lake offers limited ACID; Milvus offers none. Only Deep Lake has columnar storage, time travel, branching.

When should I choose Deep Lake over Milvus?

Choose Deep Lake for multimodal datasets shared by training and RAG; versioned computer-vision datasets; and agent memory over documents and images. Choose Milvus for billion-scale semantic and image search; RAG platforms serving many teams; and recommendation and deduplication.

Is Deep Lake or Milvus more popular?

Milvus ranks #35 on the WhichDB Score (45.9/100) and Deep Lake ranks #273 (12.2/100). Popularity is not fit: check the requirements that matter for your project.

Are Deep Lake and Milvus open source?

Yes. Deep Lake is open source. License: Apache License 2.0. Yes. Milvus is open source. License: Apache License 2.0.