Rust generally has large ecosystem, Not only Zig is early, it going to take some time for ecosystem form arround the language and become actually useful for broder audiance. Zig might be useful some folks even that this stage. So use whatever right for your situation.
HelixDB (YC X25) is a Graph vector database, where you can store both data and vector embeddings as graph nodes so your AI agents can seamlessly hybrid query on graph data and similarity search on embeddings.
Check out how you can ingest helixdb node with realtime data from kafka topic and
Stream realtime knowledge base update for AI agents and RAG applications using flink
Hey everyone, I've been working on a data pipeline to update AI agents and RAG applications’ knowledge base in real time.
Currently, most knowledgeable base enrichment is batch based . That means your Pinecone index lags behind—new events, chats, or documents aren’t searchable until the next sync. For live systems (support bots, background agents), this delay hurts.
Solution: A streaming pipeline that takes data directly from Kafka topic, generates embeddings on the fly using openai, and upserts them into Pinecone continuously. With Kafka to pinecone template , you can plug in your Kafka topic and have Pinecone index updated with fresh data.
Agents and RAG apps respond with the latest context
Recommendations systems adapt instantly to new user activity
Check out how you can run the data pipeline on apache flink with minimal configuration and would like to know your thoughts and feedback.