---
title: "Discussion on \"DuckDB Full-Text Search vs PostgreSQL FTS vs Meilisearch: 100 Million Document Index — Build Time, Query Latency, Memory\" | Hashnode"
description: "Discussion on \"DuckDB Full-Text Search vs PostgreSQL FTS vs Meilisearch: 100 Million Document Index — Build Time, Query Latency, Memory\". Can an Embedded Database Outpace a Dedicated Search Engine?\nWhen building search infrastructure, architects face a fundamental choice: specialize or consolidate. Dedicated search engines like Meilisearch excel at pure retrieval, while traditional dat..."
url: "https://hashnode.com/posts/duckdb-full-text-search-vs-postgresql-fts-vs-meilisearch-100-million-document-index-build-time-query-latency-memory/69f40003ffec263224246b88"
---

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# [DuckDB Full-Text Search vs PostgreSQL FTS vs Meilisearch: 100 Million Document Index — Build Time, Query Latency, Memory](https://novvista.hashnode.dev/duckdb-full-text-search-vs-postgresql-fts-vs-meilisearch-100-million-document-index-build-time-query-latency-memory?utm_source=hashnode&utm_medium=feed)

Can an Embedded Database Outpace a Dedicated Search Engine? When building search infrastructure, architects face a fundamental choice: specialize or consolidate. Dedicated search engines like Meilisearch excel at pure retrieval, while traditional dat...

May 1 · 3 min read · novvista.hashnode.dev  
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## Written by

[Michael Sun](https://hashnode.com/@michaelsun)

@michaelsun · San Francisco, CA

  
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Editor-in-chief at NovVista.com

I run NovVista (novvista.com), a tech publication focused on AI, developer tools, cloud infrastructure, and modern software engineering. I write signal over noise — deep-dive analysis, honest tool reviews, and practical insights for developers who build real things.

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