I built this for myself because I hated running a large ElasticSearch instance at work and wanted something that would autoscale and something that allowed for reindexing data. I also had a lot of experience running a large BigTable/Elasticsearch custom graph database I thought could be unified into a single database to cut costs. Started adding an embedding index for fun based on some Google papers and now here we are!
I have a variety of blogs that I used too and reference implementations!
It's a Rabit[Q]uantized Hierchical Balanced Clustering algorithm we use for the vector index and we use a chunked segment index for the sparse index if you're curious! Happy to discuss more!
I built this for myself because I hated running a large ElasticSearch instance at work and wanted something that would autoscale and something that allowed for reindexing data. I also had a lot of experience running a large BigTable/Elasticsearch custom graph database I thought could be unified into a single database to cut costs. Started adding an embedding index for fun based on some Google papers and now here we are!
what google papers?
Not strictly google but microsoft/bing too, here's the top ones from my notes:
https://arxiv.org/abs/2410.14452 spfresh, https://arxiv.org/abs/2111.08566 spann, https://arxiv.org/abs/2405.12497 rabitq, https://arxiv.org/abs/2509.06046 diskann,
I have a variety of blogs that I used too and reference implementations!
It's a Rabit[Q]uantized Hierchical Balanced Clustering algorithm we use for the vector index and we use a chunked segment index for the sparse index if you're curious! Happy to discuss more!
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