Weaviate vs Directus
Side-by-side trajectory, velocity, and editorial themes.
Weaviate is climbing the stack from vector database to managed memory and retrieval for agents.
Weaviate is extending beyond its vector-database core into the agentic infrastructure layer. Engram, its managed memory and context service for agents, just hit GA, while recent releases added a built-in MCP server, query profiling, and multimodal and audio support. Cloud maturity is advancing in parallel with AWS Shared Cloud GA and more granular role-based access control.
The clear direction is owning agent retrieval end to end — not just storing vectors but supplying memory, MCP-native access, and the hybrid-search quality that determines RAG outcomes. Weaviate is positioning itself as default infrastructure for agent builders, with managed cloud and access controls maturing to match enterprise expectations.
Expect Engram to gain deeper integrations with coding assistants and agent frameworks, and the 1.37 preview features (MCP server, diversity search, query profiling) to move toward GA.
Directus is staging a 12.0 major built on a reworked versioning model and tighter operational defaults
Directus is running its stable 11.17.x line while cutting release candidates for a 12.0 major. The 11.17 releases are a steady stream of editor UX, asset-caching, and AI-endpoint improvements; the 12.0 RCs carry the breaking changes that define the next major.
Two clear threads: incremental product polish in 11.17 (token-field confirmation, ETag/asset revalidation, structured-object AI endpoint, image-editor and list-view UX) and a 12.0 reset of core models — content versioning renamed from main to published, collection status replaced by an archived boolean, and operational defaults like authenticated, cached, multi-instance-shared health checks.
Expect more 12.0 release candidates consolidating the versioning and collection-settings changes with backward-compat shims before a stable 12.0, while AI endpoints (structured-object generation) keep expanding in parallel.
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