Ep66: Neo4j Data Loading at Scale + Vector Search Filtering

Hear about my hard-won lessons from loading a large-scale book dataset into Neo4j with Ollama embeddings, plus a preview of exciting new vector search features.

Highlights:

Data Loading Battle Stories

• Fixing Ollama OpenAI endpoint issues (drop the /v1 suffix!)
• Choosing embedding models with adequate context windows (nomic-embed-text: 8,192 tokens)
• Optimizing batch sizes and memory configuration
• Using EXPLAIN to identify and eliminate Cypher eager operations
• Error handling with ON ERROR CONTINUE for partial loads (achieved 83% coverage)

Neo4j 2026.01 Preview: Vector Search with Filters Three new approaches that combine vector search with Cypher filtering in a single query:

• Vector Search + Keyword Filters
• Cypher After Vector (post-filtering GraphRAG)
• Cypher Before Vector (pre-filtering on subgraphs)

No more two-step application logic for Graph RAG!

Context Graph demo app:

• Level of detail and perspectives you can view of the context graph and interactions with agents

Event

I will be at Jfokus in Stockholm next week!

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