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memvid

Free

Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.

Search ToolsFreeFree tier
Inputs: textOutputs: text
Type
Open Source
Company
Memvid
Visit Website GitHub (15.3k stars)
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About memvid

Memvid is a portable, single-file memory layer for AI agents that replaces complex RAG pipelines and vector databases. It stores data, embeddings, indices, and a crash-safe write-ahead log in a single .mv2 file, enabling sub-5ms hybrid search (BM25 + vector) and persistent memory without servers or configuration. Memvid supports time-based queries, plugs into any AI model via MCP, SDK, or API, and can be deployed locally, on-prem, or in any cloud with zero vendor lock-in. Originally created to solve a healthcare staffing problem, it has grown into an open-source platform (Apache 2.0) with over 10,000 GitHub stars, trusted by companies like ByteDance for its 93% cost savings, 35% higher accuracy, and 5ms latency on consumer hardware.

Key Features

Single-file architecture: Everything in one .mv2 file (data, embeddings, indices, WAL). No servers or databases needed.
Sub-5ms hybrid search: Combines BM25 lexical matching with semantic vector embeddings for lightning-fast retrieval.
Crash-safe embedded WAL: Deterministic write-ahead logging ensures data integrity and automatic recovery.
Time-based queries: Built-in timeline index for temporal retrieval (conversation history, time-sensitive data).
Portable and deployable anywhere: Local-first, offline-capable, on-prem, private cloud, public cloud – same file, same performance.
Plugs into your stack: Integrates via MCP, SDK, or direct API with any AI model or agent.
Zero pre-processing: Use raw data as-is, no cleanup or format conversion required.
All-in-one RAG pipeline: Embedding, chunking, retrieval, reasoning all in one file.

Pros & Cons

Pros
  • 93% cost savings on infrastructure compared to traditional vector databases
  • Sub-5ms search latency even on consumer hardware
  • 35% higher accuracy vs traditional memory methods (as claimed)
  • Portable: single file, zero vendor lock-in, deploy anywhere
  • Open-source free tier (Apache 2.0) with 50MB memory
  • Crash-safe with built-in write-ahead logging
  • Easy setup: no databases, no servers, no configuration
  • Hybrid search (BM25 + vector) for best of both worlds
Cons
  • Free tier limited to 50MB total memory, may be insufficient for large-scale applications
  • Cloud plans start at $59/month with only 1k queries per month (Starter) – may be restrictive for high-volume use
  • Relatively new product – ecosystem and community still growing
  • Limited documentation and integrations compared to mature vector databases like Pinecone or Weaviate
  • Not a full replacement for all database needs – primarily focused on AI agent memory and retrieval

Best For

Building AI agents with persistent, long-term memoryEnterprise search and knowledge managementWorkflow automation with context-aware retrievalHealthcare staffing and applicant screening (as originally intended)Conversation history retrieval for chatbots and assistantsOn-premise or air-gapped deployments needing local, private memoryReplacing complex RAG pipelines and vector databases for cost and performance gains

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FAQ

What is Memvid?
Memvid is a portable, single-file memory layer for AI agents that replaces complex RAG pipelines and vector databases. It stores data, embeddings, indices, and write-ahead log in a single .mv2 file, enabling sub-5ms hybrid search and persistent memory without servers or configuration.
How does Memvid differ from vector databases like Pinecone or Chroma?
Unlike traditional vector databases that require separate servers, configuration, and complex pipelines, Memvid is a single self-contained file that includes embedding, chunking, retrieval, and reasoning. It requires zero preprocessing, offers built-in crash-safe WAL, time-based queries, and can be deployed anywhere with no vendor lock-in.
Is Memvid free?
Yes, Memvid offers a free open-source license under Apache 2.0, which includes 50MB total memory, unlimited local queries, and basic memory creation and retrieval for local development. Cloud plans are also available starting at $59/month for more storage and features.
What are the system requirements for Memvid?
Memvid runs on consumer hardware and is local-first, offline-capable. It can be deployed on-prem, in private cloud, or public cloud. The file format is portable and works anywhere.
What types of data can I store in Memvid?
You can drop in documents, notes, conversations, or any text. Memvid automatically chunks, embeds, and indexes everything without requiring cleanup or format conversion.
How does Memvid ensure data safety?
Memvid uses a crash-safe embedded Write-Ahead Log (WAL) that ensures data integrity and automatic recovery after crashes. Identical inputs produce identical outputs.