---
title: "What Is Columnar Storage and Why Does It Make Analytics Faster?"
url: https://daily.dev/posts/what-is-columnar-storage-and-why-does-it-make-analytics-faster--8rsddrzrh
source_url: https://cratedb.com/blog/columnar-database-analytics
type: article
source: "CrateDB"
published: 2026-06-22T09:40:34.919Z
updated: 2026-06-22T09:40:58.404Z
tags: ["backend", "olap", "cratedb"]
reading_time: 10
upvotes: 0
comments: 0
language: en
---

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# What Is Columnar Storage and Why Does It Make Analytics Faster?

**[CrateDB](https://daily.dev/sources/cratedb)** · 10 min read · 0 upvotes · 0 comments

## Summary

Columnar databases store each column separately on disk, so analytical queries that access only a few columns out of many skip the rest entirely — reducing I/O by up to 95% on wide tables. This also enables better compression since similar data types are stored contiguously. The traditional trade-off between write-optimized row storage and read-optimized columnar storage historically forced teams to run two separate systems with ETL pipelines between them. CrateDB's hybrid architecture writes incoming data simultaneously to both row-based and columnar stores on the same table, letting the query planner automatically choose the optimal access path: columnar for aggregations, row-oriented for point lookups. This eliminates the need for pre-aggregation, separate data warehouses, or batch ETL steps while supporting sub-second latency on billions of rows.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://cratedb.com/blog/columnar-database-analytics>

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---

Tags: [#backend](https://daily.dev/tags/backend), [#olap](https://daily.dev/tags/olap), [#cratedb](https://daily.dev/tags/cratedb)

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