name: migrate-from-pinecone description: Migration workflow from Pinecone to Elasticsearch

Migrate from Pinecone to Elasticsearch

Use when the user wants to move from Pinecone to Elasticsearch for vector search.

1. Prompt

• Identify: index name, dimensions, and whether they use metadata filtering.
• Confirm embedding model (same model recommended for compatibility).

2. Provision

• Create an Elasticsearch index with create_index: include a dense_vector field (same dimensions as Pinecone) and any metadata fields they filter on.
• Use create_ingest_pipeline with inference for embeddings if they want server-side embedding; otherwise app-side.

3. Integrate

• Export vectors (and metadata) from Pinecone (API or export). Map to ES document shape.
• Use bulk_index to load data into Elasticsearch. Use same embedding model for queries.
• Replace Pinecone query calls with search tool using kNN query.

4. Validate

• Run the same test queries on both systems and compare top-k results.
• Tune num_candidates and size for latency/recall tradeoff.