Agent Switchboard

LanceDB vs Letta vs Milvus

Side by side, from each listing’s own data. A row where every column says the same is shown once, dimmed.

LanceDB vs Letta vs Milvus, side by side
LanceDBby LanceDBRemove LanceDB from this comparisonLettaby LettaRemove Letta from this comparisonMilvusby ZillizRemove Milvus from this comparison
Sets it apart
  • Newest listing (added Sep 2, 2026)
  • Most skills (5)
  • Streams responses
  • Only one with an MCP server
What it isStores and searches multimodal vectors in an embedded database built on the Lance columnar format, running in-process or against LanceDB Cloud.Stateful agent framework with built-in memory. Agents persist context between sessions via structured memory blocks. Formerly MemGPT. Self-hosted or managed cloud.High-performance open-source vector database with REST API, gRPC, and an official MCP server. Stores billions of vectors for semantic search, RAG, and agent memory.
ProviderLanceDBLettaZilliz
Official vendorNot an official listingSame for all
VerifiedYesSame for all
AccessAPIAPI, CLIAPI, MCP, CLI
AuthAPI KeySame for all
MCP serverNo MCP serverNo MCP serverIn its setup guide
CLI installNo CLIIn its docsIn its docs
API base URLIn its docsSame for all
SkillsVector Search, Multimodal Storage, Hybrid RetrievalPersist agent state between sessions using structured in-context memory blocks, Dynamically edit and archive memory to maintain coherent long-horizon agent behavior, Orchestrate multi-agent pipelines where agents pass typed memory between each other, Execute tool calls with full persistence of tool outputs across sessions, Deploy self-hosted or cloud agents with consistent stateful behavior at scaleVector Similarity Search, Hybrid Search, MCP Integration
StreamingNoYesNo
Push notificationsNoSame for all
CategoriesVector Databases, Memory & StateMemory & StateVector Databases
Tagsvector-search, embedded-database, lance-format, multimodal-retrieval, columnar-storage, hybrid-searchmemory, stateful-agents, memgpt, open-source, self-hosted, python, orchestrationvector-database, semantic-search, rag, mcp-server, embeddings, billion-scale, agent-memory
Listed sinceSep 2, 2026Apr 8, 2026May 13, 2026
Use it now

Share this comparison

https://agentswitchboard.dev/compare?a=lancedb&b=letta&c=milvus

More comparisons · 13

  • GitHub Copilot vs Cursor vs Codeium / Windsurf

    Three AI coding assistants, each an official listing. Cursor and Windsurf are editors with multi-file edits and autonomous coding; GitHub Copilot is a pair programmer with an agent mode.

  • LangGraph vs CrewAI vs AutoGen

    Frameworks for multi-agent systems. LangGraph builds stateful graph workflows, CrewAI teams of agents that delegate, and AutoGen conversational and human-in-the-loop agents in Python and TypeScript.

  • Mem0 vs Zep vs Letta

    Three ways to give agents long-term memory. Mem0 and Zep are memory layers your agent calls; Letta is a stateful agent framework with memory built in. Mem0 also has an MCP server.

  • Pinecone vs Qdrant vs Weaviate

    Vector databases for RAG and semantic search. Pinecone is fully managed; Qdrant and Weaviate are open source. Beyond the API, Qdrant has a CLI and Weaviate an MCP server.

  • Browserbase vs Browser Use vs Browserless

    Browsers for AI agents. Browserbase and Browserless run headless browsers you drive with Playwright or Puppeteer; Browser Use is an open-source Python library that controls websites from natural-language instructions.

  • E2B vs Daytona vs Vercel Sandbox

    Sandboxes where agents run untrusted code, each with an API and a CLI. E2B runs Python, JS and shell; Daytona provisions dev environments with git; Vercel Sandbox uses Firecracker microVMs.

  • Firecrawl vs Crawl4AI vs Jina Reader

    All three turn web pages into clean Markdown for LLMs. Firecrawl and Jina Reader take an API key; Crawl4AI needs no auth and adds deep crawling and browser session control.

  • Figma MCP Server vs Figma Context MCP vs Talk to Figma MCP

    MCP servers that bring Figma designs to coding agents. Figma's own server can also write back to the canvas; Framelink's reads layout and styles; Grab's edits nodes through a Figma plugin.

  • Ollama vs LM Studio vs vLLM

    Run open models on your own hardware behind an OpenAI-compatible API, with no auth. Ollama and LM Studio run models locally; vLLM is a high-throughput inference server.

  • Asana MCP vs ClickUp MCP vs monday.com MCP

    Official project-management MCP servers, all hosted with OAuth sign-in. monday.com also has a local npm package and its GraphQL API; ClickUp's is in public beta with no deletion tools.

  • Groq vs Cerebras Inference

    Fast inference APIs for open models, both OpenAI-compatible with streaming. Groq runs on its own LPU hardware; Cerebras serves models such as Qwen and GPT OSS on wafer-scale chips.

  • Deepgram vs AssemblyAI

    Speech-to-text APIs with real-time streaming. Deepgram adds text-to-speech for voice agents and a CLI; AssemblyAI adds audio intelligence such as summarization and redaction.

  • Neon MCP vs PlanetScale MCP

    MCP servers for managed SQL databases with branching. Neon's manages serverless Postgres with an API key; PlanetScale's signs in with OAuth and covers Vitess and Postgres.

/compare?a=lancedb&b=letta&c=milvus
3 listings side by side · "same" marks a row every column shares
listings
lancedbapiNewest listing (added Sep 2, 2026)lettaapi+cliMost skills (5); Streams responsesmilvusapi+mcp+cliOnly one with an MCP server
rows
descriptionStores and searches multimodal vectors in an embedded database built on the Lance columnar format, running in-process or against LanceDB Cloud. | Stateful agent framework with built-in memory. Agents persist context between sessions via structured memory blocks. Formerly MemGPT. Self-hosted or managed cloud. | High-performance open-source vector database with REST API, gRPC, and an official MCP server. Stores billions of vectors for semantic search, RAG, and agent memory.
providerLanceDB | Letta | Zilliz
official (same)Not an official listing
verified (same)Yes
accessAPI | API, CLI | API, MCP, CLI
auth (same)API Key
mcpNo MCP server | No MCP server | In its setup guide
cliNo CLI | In its docs | In its docs
api (same)In its docs
skillsVector Search, Multimodal Storage, Hybrid Retrieval | Persist agent state between sessions using structured in-context memory blocks, Dynamically edit and archive memory to maintain coherent long-horizon agent behavior, Orchestrate multi-agent pipelines where agents pass typed memory between each other, Execute tool calls with full persistence of tool outputs across sessions, Deploy self-hosted or cloud agents with consistent stateful behavior at scale | Vector Similarity Search, Hybrid Search, MCP Integration
streamingNo | Yes | No
push (same)No
categoriesVector Databases, Memory & State | Memory & State | Vector Databases
tagsvector-search, embedded-database, lance-format, multimodal-retrieval, columnar-storage, hybrid-search | memory, stateful-agents, memgpt, open-source, self-hosted, python, orchestration | vector-database, semantic-search, rag, mcp-server, embeddings, billion-scale, agent-memory
addedSep 2, 2026 | Apr 8, 2026 | May 13, 2026
comparisons
/compare/github-copilot-vs-cursor-vs-codeium-windsurf3 listings/compare/langgraph-vs-crewai-vs-autogen3 listings/compare/mem0-vs-zep-vs-letta3 listings/compare/pinecone-vs-qdrant-vs-weaviate3 listings/compare/browserbase-vs-browser-use-vs-browserless3 listings/compare/e2b-vs-daytona-vs-vercel-sandbox3 listings/compare/firecrawl-vs-crawl4ai-vs-jina-reader3 listings/compare/figma-mcp-server-vs-figma-context-mcp-vs-talk-to-figma-mcp3 listings/compare/ollama-vs-lm-studio-vs-vllm3 listings/compare/asana-mcp-vs-clickup-mcp-vs-monday-mcp3 listings/compare/groq-vs-cerebras-inference2 listings/compare/deepgram-vs-assemblyai2 listings/compare/neon-mcp-vs-planetscale-mcp2 listings