Mixpeek

Lucene KNN vector plugin for Elasticsearch search engine, enabling hybrid lexical+vector search, BM25 fusion, HNSW/IVF indexes for ANN. Used for enterprise search, RAG, multimodal apps. Integrated vs standalone like Weaviate: superior hybrid text handling but higher resource footprint.

Retrieval-Augmented Generation extended to handle multiple modalities including text, images, video, and audio. Uses multimodal embeddings like Gemini Embedding 2 or CLIP to enable cross-modal search and generation.

State-of-the-art multimodal embedding model from BAAI supporting text-to-image, image-to-text, and compositional visual search. Trained on the MegaPairs dataset with over 26 million retrieval triplets.

AI data lake with revolutionary index-on-the-lake technology enabling sub-second queries from S3. Features 10x cost efficiency vs in-memory DBs and 2x faster than alternatives. This is a commercial platform with OSS components.

Universal multimodal embedding model from Jina AI supporting text and images through unified pathway. Built on Qwen2.5-VL-3B-Instruct, outperforms proprietary models on visually rich document retrieval. This is a commercial API with free tier, though OSS weights available.

LanceDB is an embedded vector database built on Apache Arrow/Lance format for multimodal data, supports SQL queries, zero-copy reads, disk-based indexes like IVF-PQ. Ideal for ML pipelines and analytics; vs Chroma more columnar/multimodal focus. Features: serverless cloud, Python/Rust SDKs.