Experience split-second response times and elastic scalability with SingleStore. Boost analytics on your apps by 100x with the lightning-fast MongoDB API. Unlock the ability to create embeddings and perform semantic searches using MongoDB APIs on SingleStore.
Thanks everyone for your support so far! We believe this is the *first time* MongoDB apps will feel the speed of SingleStoreDB. You really get the scale of a distributed NoSQL database and the phenomenal analytics of an OLAP database. Icing on the cake is that SingleStoreDB can natively support vector functions that allow companies to build Generative AI applications!
About SingleStore Kai on Product Hunt
“Vector searches & 100X faster JSON analytics”
SingleStore Kai launched on Product Hunt on May 18th, 2023 and earned 122 upvotes and 53 comments, placing #8 on the daily leaderboard. Experience split-second response times and elastic scalability with SingleStore. Boost analytics on your apps by 100x with the lightning-fast MongoDB API. Unlock the ability to create embeddings and perform semantic searches using MongoDB APIs on SingleStore.
On the analytics side, SingleStore Kai competes within API, Artificial Intelligence, Data & Analytics, Data and Database — topics that collectively have 574.7k followers on Product Hunt. The dashboard above tracks how SingleStore Kai performed against the three products that launched closest to it on the same day.
Who hunted SingleStore Kai?
SingleStore Kai was hunted by Abhinav Srivastava. 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.
Abhinav Srivastava