For a scalable database for chat history, the first results are hellodigua/chatlab, groupultra/telegram-search (groupultra/telegram-search is a self-hostable tool that exports and fuzzy-searches Telegram chat history, so it fits the chat archiving category but lacks the multi-platform support and several other required features like import, attachments, and API access) and oramasearch/orama (Orama is a full-text and vector search engine that could be used as a component in a chat archiving tool, but it is not a self-contained solution for importing, storing, and searching chat messages from multiple platforms). blevesearch/bleve and prabhatsharma/zinc round out the shortlist. Compare the match explanations and check the project documentation against your requirements.
Compare the top open-source databases for chat history. Hand-picked options ranked by performance and scalability to help you find the best fit.
ChatLab is a self-hosted chat database and data pipeline designed to normalize, store, and analyze large-scale social conversation histories. It functions as an analytics platform that uses large language models to extract patterns and insights from messaging data imported from multiple platforms. The system distinguishes itself through an AI-powered analysis engine that utilizes vector-based history analysis and agent-based function calling to summarize conversation trends. It further identifies behavioral patterns by generating visual analytics, including heatmaps, word clouds, and activity
ChatLab is a self-hosted chat database and data pipeline that imports message histories from many platforms (WhatsApp, Telegram, Discord, etc.), stores them, and enables search and analysis—fitting your need for archiving and searching chats, though its emphasis on AI-driven analytics goes beyond a basic backup tool.
Telegram Search is a self-hosted platform designed to export, index, and archive personal or group message history. It functions as a private search engine that transforms scattered communication logs and media assets into a searchable knowledge library, allowing users to maintain full control over their data through containerized infrastructure. The platform distinguishes itself by utilizing vector-based semantic indexing to enable fuzzy retrieval across historical datasets. It incorporates an optical character recognition pipeline to extract text from images and media files, ensuring that v
groupultra/telegram-search is a self-hostable tool that exports and fuzzy-searches Telegram chat history, so it fits the chat archiving category but lacks the multi-platform support and several other required features like import, attachments, and API access.
Orama is a search engine and vector database that provides full-text indexing, geospatial calculations, and semantic vector storage. It functions as an LLM retrieval engine designed to provide grounded context to language models for conversational interfaces. The project implements hybrid search by combining dense vector embeddings with inverted keyword indices to retrieve documents based on both semantic meaning and exact text matches. It utilizes a WebAssembly module to execute search logic across different JavaScript environments and platforms. The system covers a broad range of retrieval
Orama is a full-text and vector search engine that could be used as a component in a chat archiving tool, but it is not a self-contained solution for importing, storing, and searching chat messages from multiple platforms.
Bleve is a search indexing engine library written in Go, designed to provide full-text search and document retrieval capabilities for embedded application data. It functions as a framework for indexing structured or unstructured information, allowing developers to build searchable collections that support complex query logic and data analysis. The engine distinguishes itself through a pluggable analysis pipeline that normalizes text before indexing, alongside support for vector similarity search to identify semantically related content. It utilizes finite-state transducer automata for efficie
Bleve is a full-text search indexing library you would embed into an application, not a self-hostable chat archiving tool that natively handles multi-platform messages, import/export, and media storage — it provides search infrastructure but lacks the ready-to-use archiving, storage, and platform integration you need.
Zinc is a high-performance full-text search engine written in Go. It provides a schema-less document index that organizes arbitrary datasets into searchable structures without requiring a predefined data format. The engine features an API compatible with Elasticsearch for indexing and querying data, which facilitates the ingestion of single and bulk records. It is designed as an in-process search engine that embeds indexing and retrieval logic within a single binary to operate with minimal system resource overhead. The system includes a built-in web-based management interface for executing s
Zinc is a self-hostable full-text search engine, which could serve as the indexing backend for a chat archiver, but it is not itself a tool for archiving, storing, and searching chat messages from multiple platforms.
Manticoresearch is a high-performance search engine and database designed for indexing and retrieving large datasets. It functions as a full-text search engine, a vector search database, and a SQL-based search database, providing a distributed search cluster architecture. The system provides an alternative to the Elasticsearch stack, offering a compatible API for indexing and searching structured and unstructured data. It distinguishes itself by supporting multiple retrieval methods, including vector matching for similarity search, geospatial queries, and traditional full-text ranking. The p
Manticore Search is a high-performance full-text search engine and database, not a ready-to-use chat archiving tool — you would need to build custom logic around it to store, search, and manage chat messages from multiple platforms, and it lacks built-in import/export or attachment handling for chat data.
This project is a full text search engine and enterprise search infrastructure designed for indexing and retrieving large sets of documents. It provides a comprehensive framework for information discovery using ranked results and linguistic analysis. The system integrates high-dimensional vector similarity search for semantic retrieval alongside traditional full-text capabilities. It distinguishes itself through support for geospatial data retrieval, multilingual text processing, and a search suggestion workflow that includes typo-tolerant query completion and spellchecking. The platform cov
Apache Lucene/Solr is a full-text search engine and enterprise search infrastructure, not a dedicated chat archiving tool — it can index chat messages but lacks the platform-specific importers, attachment storage, and backup features you need.
WCDB is a cross-platform storage layer and embedded database engine that serves as a framework for SQLite. It functions as an object relational mapper, linking application classes to database tables to enable data operations via objects rather than raw queries. The project is distinguished by an integrated encryption layer for securing data at rest and a full-text search engine that uses language-specific tokenizers for text lookups. It also features transparent field compression to reduce storage footprints and a connection-pooling model to coordinate simultaneous read and write operations a
WCDB is a cross-platform embedded database engine and ORM with full‑text search and encryption, but it is a storage library rather than a self‑hostable chat archiving tool that can import/search messages from multiple platforms.
lunr.js is a JavaScript full-text search library and client-side search engine. It creates in-memory search indexes for fast keyword retrieval and ranked document matching within browser or Node.js environments. The library utilizes a JSON serializable search index, allowing the search structure to be converted to and from JSON for storage and distribution of pre-built search data. This enables search functionality for static websites by indexing content into portable files. The system supports advanced querying capabilities, including fuzzy text matching to account for typos, field-scoped i
lunr.js is a pure full-text search library for JavaScript, not a self-hostable chat archiving tool — it provides the search engine component but does not handle storing chat messages, attachments, or import/export, so while it could be used as part of a larger solution, it is not the complete tool this search requires.
Karakeep is a self-hosted, open-source platform designed for personal knowledge management and web content archiving. It functions as a centralized repository where users can capture, organize, and preserve bookmarks, notes, and media files, ensuring long-term access to digital information even if original sources are removed or modified. The system distinguishes itself through its automated content processing and security-focused architecture. It utilizes headless browser crawling and optical character recognition to ingest and index web content, while a modular artificial intelligence pipel
Karakeep is a self-hosted web content/bookmark archiver rather than a chat message backup tool, so it lacks the multi-platform messaging support this search requires.
SQLite is a serverless relational database engine and C-based library that stores data in a single local disk file. It functions as an embedded SQL database, integrating directly into applications without the need for a separate server process. The engine includes specialized capabilities for full-text search indexing and spatial data querying using R-Tree structures for geographic or geometric coordinate ranges. The system provides broad support for SQL data manipulation, database recovery and repair, and change tracking for synchronizing modifications between databases. It also features a
SQLite is an embedded database engine with full-text search, but it is a building block rather than a complete chat archiving tool that captures messages from multiple platforms, stores attachments, and provides import/export and API access.
WildfireChat’s im-server is an open-source instant messaging backend that handles message routing, user management, and group chat for private deployments. It provides a self-hosted messaging platform that can run on private infrastructure without third-party cloud dependencies, supporting enterprise messaging with group management, user directories, and external system integration. The server synchronizes messages and state across mobile, desktop, web, and mini-program clients simultaneously, and supports real-time audio/video calls with group conferencing and live streaming. It includes enc
WildfireChat's im-server is an instant messaging backend for running your own real-time chat platform, not a dedicated archiving tool for importing messages from external services like Slack or WhatsApp, so it lacks the multi-source import and retrospective search focus you are looking for.
| Repository | Stars | Language | License | Last push |
|---|---|---|---|---|
| hellodigua/chatlab | 4.5K | TypeScript | agpl-3.0 | |
| groupultra/telegram-search | 3.9K | TypeScript | AGPL-3.0 | |
| 10.4K |
| TypeScript |
| NOASSERTION |
| blevesearch/bleve | 11K | Go | apache-2.0 |
| prabhatsharma/zinc | 17.9K | Go | NOASSERTION |
| manticoresoftware/manticoresearch | 11.8K | C++ | GPL-3.0 |
| apache/lucene-solr | 4.4K | — | Apache-2.0 |
| tencent/wcdb | 11.5K | C | NOASSERTION |
| olivernn/lunr.js | 9.2K | JavaScript | MIT |
| karakeep-app/karakeep | 26.2K | TypeScript | AGPL-3.0 |