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StackGrep Engine vs Elasticsearch

Elasticsearch is a distributed search and analytics engine you run as a cluster (or rent as Elastic Cloud), with BM25 ranking, aggregations and a large ecosystem. StackGrep Engine is something else: exact text and regex search over your own documents, built for AI agents, with every match counted and your index kept in object storage.

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What StackGrep does differently

  • Regex runs across the whole text of a document, not one indexed word at a time
  • No nodes, shards or mappings to size: create a collection and push JSON
  • Your index lives in object storage, so idle data costs storage, not always-on nodes
  • A hosted MCP server, so agents search it without glue code

When Elasticsearch is the better pick

If you need relevance-ranked full-text search, aggregations and dashboards, or you already run a cluster and know it well.

Three calls to try it

POST /api/collections/docs/docs     {"docs": [{"id": "a1", "text": "...", "meta": {"team": "ops"}}]}
GET  /api/collections/docs/search?q=net+30&filter=team:ops
GET  /api/collections/docs/count?q=net+30

Quickstart →

Questions

Is StackGrep a drop-in Elasticsearch replacement?

No. It doesn't rank by relevance or run aggregations. It finds exact text and regex matches, filters by metadata and counts exactly, which is what most agent lookups need.

Can StackGrep do log search?

Yes, for finding lines by exact text or pattern: push logs or point us at the bucket they land in. For charts and alerting on metrics, use a logging tool.

Other comparisons

Use cases

Give your agents exact search

StackGrep Engine is onboarding teams from the waitlist. Bring your documents or your bucket.

Join the waitlist Read the docs