You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Qdrant, similar to Elasticsearch or Pinecone is a popular vector database.
We use qdrant for various vector search tasks. These vectors are created based on text values stored in Postgres. We need to be able to make sure parts of Postgres are synced with qdrant to enable good vector search in our product. A lot of AI products are dependent on this and should be a highly relevant use case for the Estuary team.
The text was updated successfully, but these errors were encountered:
This is definitely a system we target a native integration with. In the meantime, perhaps it would be possible to use the Kafka connect connector and our Dekaf broker? We haven't tried it out but that likely would work.
System Name
Qdrant
Type
Materialize
Details
Qdrant, similar to Elasticsearch or Pinecone is a popular vector database.
We use qdrant for various vector search tasks. These vectors are created based on text values stored in Postgres. We need to be able to make sure parts of Postgres are synced with qdrant to enable good vector search in our product. A lot of AI products are dependent on this and should be a highly relevant use case for the Estuary team.
The text was updated successfully, but these errors were encountered: