StrataFS vs. Elasticsearch for semantic code search — when each makes sense
Elasticsearch is the workhorse of full-text search. StrataFS is the new workhorse of embedded semantic search. Here's an honest comparison for developer-focused use cases.
Long-form writing on hybrid retrieval, MCP, SQLite-as-search-engine, and the architectural choices behind StrataFS.
Elasticsearch is the workhorse of full-text search. StrataFS is the new workhorse of embedded semantic search. Here's an honest comparison for developer-focused use cases.
Wire StrataFS into Claude Desktop in five minutes. Hybrid search across your code and docs becomes a tool Claude knows how to call. Step-by-step, with the config and the troubleshooting.
Indexing cloud storage used to mean pipelines, copies, and a separate search service. StrataFS reads buckets in place with read-only credentials and exposes a hybrid search across all of them.
Most 'AI search' tools want your data on their servers. We didn't want to send our files anywhere, so we built StrataFS. Here's the case for self-hosted semantic search.
The 'embedded search server' used to be a contradiction. With SQLite FTS5 for BM25 and sqlite-vec for cosine similarity, both indexes live in one file — and one SQL query fuses them.
Hybrid search isn't a gimmick — it solves real failure modes of pure BM25 and pure vector retrieval. Here's the math, the SQL, and the tuning knobs that matter.
The Model Context Protocol is the USB-C of agent integrations — but most MCP servers stop at the protocol. StrataFS goes further: hybrid retrieval, pre-shaped responses, per-source isolation, all local.
Grep is precise but literal. Semantic code search finds the file you mean, not the file you spelled. Here's why hybrid retrieval beats either alone — and how to run it locally with StrataFS.
MIT-licensed. Multi-storage. Native MCP server for AI agents. Local, S3, GCS, Azure, SharePoint, Drive and Jira.