One container. 4 cores. Hybrid search. 10k concurrent users?
Transparent benchmarking of a single-container hybrid search setup on consumer hardware.

WMTR tokenizer handles SKUs and part numbers where Elasticsearch chokes.
Teams building RAG pipelines or enterprise search
Weaviate · Qdrant · Meilisearch
Transparent benchmarking of a single-container hybrid search setup on consumer hardware.
Hooks into MCP (Claude Desktop, Ollama, etc.) and keeps everything on disk — auto-saved chats, Slack/Notion imports, and file ingestion make it useful right away for local-agent workflows. The hybrid retrieval combo (graph + vector + keyword) without requiring an external vector DB is an interesting engineering choice, but the space is crowded and I want benchmarks and failure-mode details before recommending it for production.
Exports a one-file 'brain' and a tiny MemoryOrchestrator API (remember/recall) so you can ditch Docker and hosted vector DBs — token-budgeted, deterministic recall and kill-9-safe durability are concrete wins. The Metal-accelerated vector search plus SQLite FTS5 fallback shows real engineering heft, but it's clearly tuned for the Apple ecosystem and the author is still asking for retrieval/eval feedback.
Local RAG without cloud: sync your codebase, search hybrid, feed Cursor via MCP.
Orthogonal matrix encryption preserves cosine similarity while keeping embeddings private.
Stripped cluster logic from Amgix to build a single-binary Rust engine that crushes latency benchmarks.