In the news
Full Text Search in SmithDB: Designing an Inverted Index for Object Storage
LangChain · Published · 3 min read
In 30 seconds
- What happened
- LangChain's SmithDB built a specialized inverted index for full-text search over large JSON agent traces stored in object storage with 400ms median latency.
- Why it matters
- Engineers building search systems over large semi-structured data in cloud object storage need efficient indexing strategies that account for storage latency constraints.
- Watch out
- The design trades off against traditional search libraries like Tantivy because object storage has fundamentally different I/O economics than local disk with mmap access patterns.
Listen to this summary
- agent
- rag
- latency
The patterns behind this
- Agentic Context Engineering (Evolving Playbook)
- Structure-Aware Codebase Retrieval (Repo Map)
- Hierarchical Index Retrieval (RAPTOR)
Each one covers how the technique works, when it earns its cost, and where it breaks.
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