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Firebase Vector Search

Firebase vector search made easy

Developer Tools
Artificial Intelligence
GitHub
Database
Visit WebsiteSee on Product Hunt

Hunted bynuricnuric

SemaDB Firebase extension is a bridge between Firestore and SemaDB to enable easy vector search across documents. It syncs document vectors stored in Firestore and provides a vector search endpoint.

Top comment

Hello Product Hunt Community 👋 Firebase is great but it doesn’t have in-built search, let alone vector search. With a growing number of potential applications, AI models are becoming more important and require vector based search to enable solutions such as semantic search, retrieval-augmented generation and product recommendations. We are excited to bring an easy-to-use, fully-hosted vector search extension to your Firebase projects. 1. Install with one click from the Firebase Extensions hub. 2. Sync your document vectors to SemaDB automatically. 3. Perform vector search 🔍 with an integrated Firebase cloud function. The extension never shares your data, just the vector representation and stores the Firestore document ID in SemaDB. You can choose which Firestore and SemaDB collections to sync as well as the vector field. To get started, you only need to create a collection in SemaDB cloud with the desired vector size and distance metric, then install the Firebase extension 🚀

Comment highlights

What a great product! Congratulations! I just tried it, this is one of the most useful tools on PH!! This deserves no 1!

About Firebase Vector Search on Product Hunt

Firebase vector search made easy

Firebase Vector Search launched on Product Hunt on November 26th, 2023 and earned 110 upvotes and 9 comments, placing #14 on the daily leaderboard. SemaDB Firebase extension is a bridge between Firestore and SemaDB to enable easy vector search across documents. It syncs document vectors stored in Firestore and provides a vector search endpoint.

Firebase Vector Search was featured in Developer Tools (512.5k followers), Artificial Intelligence (468.6k followers), GitHub (41.2k followers) and Database (2.1k followers) on Product Hunt. Together, these topics include over 184k products, making this a competitive space to launch in.

Who hunted Firebase Vector Search?

Firebase Vector Search was hunted by nuric. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

Want to see how Firebase Vector Search stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.