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    <title>Bleve on Shaharia Azam&#39;s Website | DevOps, Platform Engineering &amp; AI Insights</title>
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    <description>Recent content in Bleve on Shaharia Azam&#39;s Website | DevOps, Platform Engineering &amp; AI Insights</description>
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      <title>Embeddable Vector Database for Go — chromem-go, Bleve, sqlite-vec compared</title>
      <link>https://shaharia.com/blog/choosing-embeddable-vector-database-go-application/</link>
      <pubDate>Sat, 25 Apr 2026 00:00:00 +0000</pubDate>
      <guid>https://shaharia.com/blog/choosing-embeddable-vector-database-go-application/</guid>
      <description>TL;DR — if you just want the answer&#xA;&amp;lt; ~100k vectors, pure-Go, no CGO, want it to &amp;ldquo;just work&amp;rdquo;: use chromem-go. Lexical + vector search in one engine, pure-Go: use Bleve. Millions of vectors, OK with CGO, SQL filters: use sqlite-vec (via mattn/go-sqlite3) or DuckDB + VSS. You can run a separate process: stop reading — use Qdrant or Chroma server. The whole point of this post is the single-binary constraint below.</description>
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