need vector database for images and text together

If you want one vector database for both images and text, you’re looking for a multimodal vector DB or a normal vector DB that can store embeddings from different models in the same index/collection.

Good options

1) Pinecone

• Easy managed service
• Works well for text and image embeddings
• Good metadata filtering
• Best if you want low ops overhead

2) Weaviate

• Strong multimodal support
• Can store text, image, and metadata together
• Good for semantic search across modalities
• Open-source + cloud

3) Qdrant

• Very flexible
• Supports named vectors, so you can keep text and image embeddings separately in the same collection
• Great filtering and performance
• Open-source + cloud

4) Milvus

• Scales well
• Supports multimodal use cases
• Good if you need large-scale vector search
• More infra-heavy than Pinecone/Qdrant

5) Postgres + pgvector

• Good for smaller systems
• Can store text/image embeddings in tables
• Simple if you already use PostgreSQL
• Not ideal for very large-scale ANN search compared to dedicated vector DBs

Best approach

For images + text, usually you do this:

• Convert text to text embeddings
• Convert images to image embeddings
• Store them in the same DB with:
  • a shared item ID
  • modality type (text, image)
  • metadata
• Query with the same embedding space if using a multimodal model like CLIP

Important note

If you want search text to find images or image to find text, use a model that maps both into the same vector space, like:

• CLIP
• SigLIP
• multimodal embedding models from OpenAI / others

If you use separate embedding models for text and images, you can still store them together, but cross-modal search is harder unless you align the spaces.

My recommendation

• Fastest to build: Pinecone
• Best open-source multimodal choice: Weaviate or Qdrant
• Best for cross-modal search: use CLIP-style embeddings + one of the above

If you want, I can give you:

1. a comparison table
2. a recommended stack for your use case
3. example code for storing/searching images + text