Marqo is more than a vector database, it's an end-to-end vector search engine. Vector generation, storage and retrieval are handled out of the box through a single API. No need to bring your own embeddings.
Marqo CloudOpen SourceWith Marqo, input pre-processing, machine learning inference, and storage are all included out of the box.
Run Marqo in a docker image on your laptop or scale it up to dozens of GPU inference nodes in the cloud. Marqo can be scaled to provide low latency searches against multi-terabyte indexes.
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Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images. You can seamlessly search any combination of text and images and even combine text and images into a single vector.
Marqo has you covered from inference to storage. With Marqo you don't need to calculate the vectors yourself, simply select the model you want to use and pass the text and/or image URLs directly to the API.
Vector search allows you to go beyond keyword matching and lets you search based on the meaning of text, images and other unstructured data.
Marqo provides a feature rich developer experience - it lets you perform multimodal vector search without having to sacrifice on features like filtering and highlighting.
Marqo can be used with text and/or image data. Multimodal indexes seamlessly handle image-to-image, image-to-text and text-to-image search.
Marqo supports weighted queries which can combine multiple text and image queries together. Negative weights can be added to query terms to push certain items out of your result set.
Marqo supports score modifiers, numeric fields in your documents can be used to manipulate the score and influence the ranking of results.
Additional context can be added to queries by providing vectors directly, this helps tailor results without the overhead of additional inference.
Import open source models from Hugging Face, bring your own, or load private models from AWS S3 or Hugging Face using authentication.
Parts of Marqo's API support bulk operations to improve throughput. These bulk operations enable use cases such as bulk changes to multiple indexes or coalescing of queries.
Marqo is horizontally scalable and can be run at million document scale whilst maintaining lightning-fast search times.
Marqo provides search highlighting functionality which allows you to transparently understand where and why a match occurred.
Marqo offers a powerful query DSL (Domain Specific Language), which can be applied as a prefilter ahead of approximate k-NN search.
Get involved with building the future of Marqo or access support from Marqo's vast community by joining us on Slack and Github.
Join our discourse forum to keep up with the latest announcements, troubleshoot with the community, or show off something you have built with Marqo!
