Biblos supports semantic Bible search and layered analysis through a GitHub project.
Chroma
Chroma provides open source search infrastructure for AI applications.
About Chroma
Chroma provides search infrastructure for AI applications, supporting vector, sparse vector, full-text, regex, and metadata search. It can be used through Cloud or run locally, with client examples for Python, TypeScript, and Rust.
The system stores vectors, metadata, and indexes on object storage with memory and SSD caching tiers. Published specifications list limits including 1M collections per database, 5M records per collection, and per-collection throughput and concurrency figures.
Key features
- Vector search for semantic similarity
- Sparse vector search using BM25 and SPLADE
- Full-text search with trigram and regex
- Metadata filtering and faceted search
- Dataset versioning for A/B testing and rollouts
- Command-line tools for development tasks
Best for: Developers building AI applications that need combined vector, text, and metadata search.
Good for
- Combines vector, full-text, regex, and metadata search in one system
- Can run locally or on Cloud with automatic scaling and no manual tuning
- Supports BYOC deployment in a customer VPC with multi-region replication
Watch out for
- Published specs list a limit of 5M records per collection
- Published latency table shows higher latency for cold queries than warm queries
- Published specs list per-collection throughput and concurrent read limits
Chroma at a glance
- Website
- trychroma.com
- Category
- AI & Machine Learning › AI Search & Research
- Type
- Online tool
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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