Adding Semantic Search to an Existing DynamoDB Table with Vector Indexes

<p>Some time ago at my work, we had to implement a small search engine for help articles. The search was very simple: it used lexical, prefix-based matching. This was a problem

<p>Most semantic search systems don’t fail because of embeddings. They fail because of how the system is designed around them.</p> <p>When I started building a semantic search API

<h2> 🎯 Who This Is For </h2> <ul> <li>You want to store and search vector data in DynamoDB</li> <li>You're frustrated that a single query returns at most 100 results, which leaves

<!-- SC_OFF --><div class="md"><p>Hi Reddit, we are a team of database researchers (including a PhD from MIT DB Group) and we just open-sourced an embedded vector database for

<h1> Vector Search &amp; Embeddings in Java: Building Semantic Search Engines </h1> <h2> Introduction </h2> <p>Traditional keyword-based search is dead. When users search for

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<p>How I built browser-native semantic vector search using WASM — no server, no API keys, no per-query cost. Full code walkthrough with React. </p> <p>My documentation site had

<p>Simple, keyword-based database queries are often inadequate for user searches because they struggle with complexities such as synonyms, slang, and relevance judgments. They