SynapCores Lets LlamaIndex Run Vector and Graph Indexes on One Engine

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Developers using LlamaIndex typically need two separate backends — a vector store and a graph database — to support both VectorStoreIndex and PropertyGraphIndex. SynapCores is a single engine that now supports both index types through two independently published LlamaIndex integration packages on PyPI. The vector store implements the full BasePydanticVectorStore interface, including all 12 metadata filter operators and async support, while the graph store implements the full PropertyGraphStore interface with both structured and vector query capabilities. Both index types connect to the same SynapCores instance via a single URI, eliminating the need for cross-service synchronization. The integration is backed by 48 automated tests run against a live engine via Docker Compose, with source code and notebooks available on GitHub.

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