Show HN: Embeddinghub: A vector database built for Machine Learning embeddings
1–10 of 35 posts
Re: Show HN: Embeddinghub: A vector database built for Machine Learning embeddings
#2Over the years, I've found myself building hacky solutions to serve and manage my embeddings. I’m excited to share Embeddinghub, an open-source vector database for ML embeddings. It is built with four goals in mind:
Store embeddings durably and with high availability
Allow for approximate nearest neighbor operations
Enable other operations like partitioning, sub-indices, and averaging
Manage versioning, access control, and rollbacks painlessly
It's still in the early stages, and before we committed more dev time to it we wanted to get your feedback. Let us know what you think and what you'd like to see!
Repo: https://github.com/featureform/embeddinghub
Docs: https://docs.featureform.com/
What's an Embedding? The Definitive Guide to Embeddings: https://www.featureform.com/post/the-definitive-guide-to-emb...
Re: Show HN: Embeddinghub: A vector database built for Machine Learning embeddings
#3Hi everyone! Over the years, I've found myself building hacky solutions to serve and manage my embeddings. I’m excited to share Embeddinghub, an open-source vector database for ML embeddings. It is built with four goals in mind: Store embeddings durably and with high availability Allow for approximate nearest neighbor operations Enable other operations like partitioning, sub-indices, and averaging Manage versioning,…
I see you've got examples for NLP use cases in your docs. Can't wait to read them. Embeddings are a constant source of complexity when I'm trying to move certain operations to Lambda, this looks like it would speed the initializations up big time.
Re: Show HN: Embeddinghub: A vector database built for Machine Learning embeddings
#4Re: Show HN: Embeddinghub: A vector database built for Machine Learning embeddings
#5which search algorithm does it use?
Re: Show HN: Embeddinghub: A vector database built for Machine Learning embeddings
#6Hi everyone! Over the years, I've found myself building hacky solutions to serve and manage my embeddings. I’m excited to share Embeddinghub, an open-source vector database for ML embeddings. It is built with four goals in mind: Store embeddings durably and with high availability Allow for approximate nearest neighbor operations Enable other operations like partitioning, sub-indices, and averaging Manage versioning,…
Holy shit, this looks amazing! I see you've got examples for NLP use cases in your docs. Can't wait to read them. Embeddings are a constant source of complexity when I'm trying to move certain operations to Lambda, this looks like it would speed the initializations up big time.
Re: Show HN: Embeddinghub: A vector database built for Machine Learning embeddings
#7Hi everyone! Over the years, I've found myself building hacky solutions to serve and manage my embeddings. I’m excited to share Embeddinghub, an open-source vector database for ML embeddings. It is built with four goals in mind: Store embeddings durably and with high availability Allow for approximate nearest neighbor operations Enable other operations like partitioning, sub-indices, and averaging Manage versioning,…
Re: Show HN: Embeddinghub: A vector database built for Machine Learning embeddings
#8Re: Show HN: Embeddinghub: A vector database built for Machine Learning embeddings
#9Specifically around nearest neighbor computation latency, a regular get embedding latency, read/write rate achieved on a machine?