--- title: "deeplake vs lancedb" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/activeloopai-deeplake-vs-lancedb-lancedb" tools: ["activeloopai-deeplake", "lancedb-lancedb"] --- # deeplake vs lancedb *GraphCanon updated Aug 17, 2026* ## Verdict Pick deeplake if deeplake is an AI Data Runtime for Agents designed with serverless Postgres and multimodal data lake support, targeting scalable retrieval and training capabilities; pick lancedb if lanceDB is a developer-friendly, open-source embedded retrieval library for multimodal AI applications. It supports various SDKs and REST APIs, offering efficient functionalities including approximate nearest neighbor (k. [deeplake](https://deeplake.ai) reports 9.2k GitHub stars, 721 forks, and 63 open issues, last pushed May 21, 2026. [lancedb](https://lancedb.com/docs) has 11k stars, 972 forks, and 630 open issues, last pushed Jul 28, 2026. Figures are from public GitHub metadata via [deeplake's repository](https://github.com/activeloopai/deeplake) and [lancedb's repository](https://github.com/lancedb/lancedb). | | [deeplake](/tools/activeloopai-deeplake.md) | [lancedb](/tools/lancedb-lancedb.md) | | --- | --- | --- | | Tagline | AI Data Runtime for Agents with scalable retrieval and training features | Developer-friendly OSS embedded retrieval library for multimodal AI. | | Stars | 9,224 | 11,014 | | Forks | 721 | 972 | | Open issues | 63 | 630 | | Language | C++ | Rust | | Adopt for | Deeplake is an AI Data Runtime for Agents designed with serverless Postgres and multimodal data lake support, targeting scalable retrieval and training capabilities. | LanceDB is a developer-friendly, open-source embedded retrieval library for multimodal AI applications. It supports various SDKs and REST APIs, offering efficient functionalities including approximate nearest neighbor (k | | Persona | - | - | | Runtime | - | - | | License | Deeplake uses the Apache-2.0 license, allowing free use in both open source and commercial projects with attribution. | Apache-2.0 | | Categories | Data & Retrieval, Model Training, Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [deeplake](/tools/activeloopai-deeplake.md) | [lancedb](/tools/lancedb-lancedb.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 87d | 0d | | Open issues (now) | 63 | 630 | | Stars delta | +16 (30d) | Unknown | | Open issues delta | -6 (30d) | Unknown | | Full report | [trust report](/tools/activeloopai-deeplake/trust.md) | [trust report](/tools/lancedb-lancedb/trust.md) | ## Shared compatibility - **Python**: [deeplake](/tools/activeloopai-deeplake.md) - Python runtime; [lancedb](/tools/lancedb-lancedb.md) - Python runtime ## Decision facts: deeplake - **Pricing:** unknown - Pricing details are not specified for Deeplake's public repository. - **Requirements:** Deeplake can be installed using pip, making it accessible via the command `pip install deeplake`. - **Adopt for:** Deeplake is an AI Data Runtime for Agents designed with serverless Postgres and multimodal data lake support, targeting scalable retrieval and training capabilities. - **License detail:** Deeplake uses the Apache-2.0 license, allowing free use in both open source and commercial projects with attribution. ## Decision facts: lancedb - **Pricing:** freemium - Open-source under Apache-2.0 license, ensuring free use and modification for everyone. - **Adopt for:** LanceDB is a developer-friendly, open-source embedded retrieval library for multimodal AI applications. It supports various SDKs and REST APIs, offering efficient functionalities including approximate nearest neighbor (k ## Choose when ### Choose deeplake if… - deeplake is primarily C++; lancedb is Rust. - Pricing: Pricing details are not specified for Deeplake's public repository.. - Requirements: Deeplake can be installed using pip, making it accessible via the command `pip install deeplake`.. - Tags unique to deeplake: agent, agentic-rag, ai, computer-vision. - Also covers Model Training. - When you are developing applications that require seamless integration with AI agents, as Deeplake supports agent-centric design. ### Choose lancedb if… - lancedb is primarily Rust; deeplake is C++. - Pricing: Open-source under Apache-2.0 license, ensuring free use and modification for everyone.. - Tags unique to lancedb: approximate-nearest-neighbor-search, image-search, nearest-neighbor-search, recommender-system. - lancedb ships Docker support for self-hosted deployment. - - When you need an easy-to-use, fully featured search functionality, encompassing approximate nearest neighbor searches, image searches, semantic searches, etc., specifically tailored for multimodal A ## When NOT to use deeplake - If your project does not benefit from an agent-centric architecture and you primarily require traditional database operations without multimodal features. - When cost control is critical and serverless PostgreSQL might introduce variable costs compared to on-premises solutions for data retrieval and training. ## When NOT to use lancedb - - Avoid LanceDB if your project requires real-time search latency below millisecond levels because the overhead for embedding storage and retrieval might affect performance. - - Not suitable when you are working with large-scale real-time applications that require extensive horizontal scalability beyond what its embedded design can offer. ## Common questions ### What is the difference between deeplake and lancedb? deeplake: AI Data Runtime for Agents with scalable retrieval and training features. lancedb: Developer-friendly OSS embedded retrieval library for multimodal AI.. See the comparison table for live GitHub stats and shared categories. ### When should I choose deeplake over lancedb? Choose deeplake over lancedb when deeplake is primarily C++; lancedb is Rust; Pricing: Pricing details are not specified for Deeplake's public repository.; Requirements: Deeplake can be installed using pip, making it accessible via the command `pip install deeplake`.; Tags unique to deeplake: agent, agentic-rag, ai, computer-vision; Also covers Model Training; When you are developing applications that require seamless integration with AI agents, as Deeplake supports agent-centric design. ### When should I choose lancedb over deeplake? Choose lancedb over deeplake when lancedb is primarily Rust; deeplake is C++; Pricing: Open-source under Apache-2.0 license, ensuring free use and modification for everyone.; Tags unique to lancedb: approximate-nearest-neighbor-search, image-search, nearest-neighbor-search, recommender-system; lancedb ships Docker support for self-hosted deployment; - When you need an easy-to-use, fully featured search functionality, encompassing approximate nearest neighbor searches, image searches, semantic searches, etc., specifically tailored for multimodal A. ### When should I avoid deeplake? If your project does not benefit from an agent-centric architecture and you primarily require traditional database operations without multimodal features. When cost control is critical and serverless PostgreSQL might introduce variable costs compared to on-premises solutions for data retrieval and training. ### When should I avoid lancedb? - Avoid LanceDB if your project requires real-time search latency below millisecond levels because the overhead for embedding storage and retrieval might affect performance. - Not suitable when you are working with large-scale real-time applications that require extensive horizontal scalability beyond what its embedded design can offer. ### Is deeplake or lancedb more popular on GitHub? lancedb has more GitHub stars (11,014 vs 9,224). Stars measure visibility, not whether either tool fits your constraints. ### Are deeplake and lancedb open source? Yes - both are open-source projects on GitHub (deeplake: Apache-2.0, lancedb: Apache-2.0). ### Where can I find alternatives to deeplake or lancedb? GraphCanon lists graph-backed alternatives at [deeplake alternatives](/tools/activeloopai-deeplake/alternatives) and [lancedb alternatives](/tools/lancedb-lancedb/alternatives) ([deeplake markdown twin](/tools/activeloopai-deeplake/alternatives.md), [lancedb markdown twin](/tools/lancedb-lancedb/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/activeloopai-deeplake-vs-lancedb-lancedb.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, deeplake or lancedb? deeplake: Steady. lancedb: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for deeplake and lancedb? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [deeplake trust report](/tools/activeloopai-deeplake/trust); [lancedb trust report](/tools/lancedb-lancedb/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=activeloopai-deeplake`](/api/graphcanon/graph?tool=activeloopai-deeplake) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_