contextdb

Bases de datos vectoriales

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ContextDB is an embedded database designed to unify agentic memory by seamlessly integrating relational, graph, and vector search capabilities within a single transaction and file, enabling efficient management of structured data, relationships, and similarity searches. Its main features include native support for SQL with deterministic upsert and secondary indexing, built-in graph traversal using bounded breadth-first search, and native vector search with algorithms like HNSW for cosine similarity, addressing complex data retrieval, relationship mapping, and similarity matching problems for AI agents and applications; it is ideal for developers and organizations seeking an open-source, low-latency, in-process memory solution for scalable, shared, and collective intelligence deployments.

contextdb se puede encontrar en Vector Databases categorías.

Los productos más similares a contextdb son:

DrawSQL Promocionado → VectorScaleDB Perfil verificado → Turso → YDB → SlashDB →

Capturas de pantalla

Detalles

Características principales de contextdb

• Open Source
  The database code is free and available for everyone to use and change.
• Graph Search
  It can find relationships and move through data like a network with traversal.
• Vector Search
  It can find similar items using embedding vectors and similarity measures.
• Native Support
  It has built-in features for graph traversal and vector search, not just basic storage.
• Unified Engine
  All three types of search work together in one engine with the same API.
• One Transaction
  All the searches and storage happen in a single transaction for easy management.
• Storage Options
  You can use local storage or cloud storage like S3 in the managed platform.
• Embedded Database
  It is a small database that stores memory for agents inside one file and runs inside your app.
• Relational Search
  It can store and search data using tables, metadata, and structured queries.
• Multiple Search Types
  It can do relational search, graph search, and vector search all in one place.
• Sync and Connectivity
  It can connect edge devices and servers securely and automatically.
• Collective Intelligence
  Multiple deployments can share learnings to make the system smarter.
• Managed Platform Features
  The managed platform offers easy deployment, sync between multiple users, and collective learning.
• Single File and In-Process
  It runs inside your app as one file, making it simple to use.
• Transactions and Snapshots
  It supports safe transactions and consistent snapshots of data.
• Open Source vs Managed Platform
  You can use the open-source version or the managed platform, which handles updates and deployment.

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VectorScaleDB

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Turso

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YDB

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SlashDB

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Tecnologías utilizadas

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