<!-- mobian-agent-page publisher="dailydev" canonical="https://daily.dev/posts/building-a-weather-data-warehouse-part-i-loading-a-trillion-rows-of-weather-data-into-timescaledb-6wdb9ia7f" -->

---
title: Building a weather data warehouse part I: Loading a...
description: The post discusses the process of building a weather data warehouse using PostgreSQL and TimescaleDB. It explores the need for historical weather data, the...
canonical: https://daily.dev/posts/building-a-weather-data-warehouse-part-i-loading-a-trillion-rows-of-weather-data-into-timescaledb-6wdb9ia7f
twitter:card: summary_large_image
twitter:site: @dailydotdev
og:type: website
og:site_name: daily.dev
og:title: Building a weather data warehouse part I: Loading a trillion rows of weather data into TimescaleDB | daily.dev
og:description: The post discusses the process of building a weather data warehouse using PostgreSQL and TimescaleDB. It explores the need for historical weather data, the...
og:url: https://daily.dev/posts/building-a-weather-data-warehouse-part-i-loading-a-trillion-rows-of-weather-data-into-timescaledb-6wdb9ia7f
og:image: https://api.daily.dev/og/posts/6WDb9IA7F.png
og:image:alt: Building a weather data warehouse part I: Loading a trillion rows of weather data into TimescaleDB
og:image:width: 1200
og:image:height: 630
og:locale: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Building a weather data warehouse part I: Loading a trillion rows of weather data into TimescaleDB

**[Hacker News](https://daily.dev/sources/hn)** · 15 min read · 2 upvotes · 0 comments

## Summary

The post discusses the process of building a weather data warehouse using PostgreSQL and TimescaleDB. It explores the need for historical weather data, the ERA5 climate reanalysis product, and the challenges of loading large amounts of data into a database. The post compares different insertion methods, including single-row inserts, multi-valued inserts, and the copy statement. It also evaluates the performance of external tools like pg_bulkload and timescaledb-parallel-copy. The conclusion suggests using psycopg3 to directly copy data into a hypertable or using timescaledb-parallel-copy if CSV files are available. The post provides detailed benchmarks and considerations for achieving optimal insert rates and loading times.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://aliramadhan.me/2024/03/31/trillion-rows.html>

---

Tags: [#postgresql](https://daily.dev/tags/postgresql), [#data-warehouse](https://daily.dev/tags/data-warehouse), [#timescaledb](https://daily.dev/tags/timescaledb)

[View this post on daily.dev](https://daily.dev/posts/building-a-weather-data-warehouse-part-i-loading-a-trillion-rows-of-weather-data-into-timescaledb-6wdb9ia7f)

```json
{"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]}
{"@context":"https://schema.org","@type":"TechArticle","headline":"Building a weather data warehouse part I: Loading a trillion rows of weather data into TimescaleDB","url":"https://daily.dev/posts/building-a-weather-data-warehouse-part-i-loading-a-trillion-rows-of-weather-data-into-timescaledb-6wdb9ia7f","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/building-a-weather-data-warehouse-part-i-loading-a-trillion-rows-of-weather-data-into-timescaledb-6wdb9ia7f"},"datePublished":"2024-04-16T14:09:24.407Z","dateModified":"2024-05-09T09:28:18.744Z","description":"The post discusses the process of building a weather data warehouse using PostgreSQL and TimescaleDB. It explores the need for historical weather data, the...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/ab4889ebe97c215c71c9abd7c469ab1a?_a=AQAEufR","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/ab4889ebe97c215c71c9abd7c469ab1a?_a=AQAEufR","isAccessibleForFree":true,"articleSection":"Hacker News","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Hacker News","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/hn","url":"https://daily.dev/sources/hn"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/building-a-weather-data-warehouse-part-i-loading-a-trillion-rows-of-weather-data-into-timescaledb-6wdb9ia7f","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":2},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"postgresql,data-warehouse,timescaledb","timeRequired":"PT15M"}
{"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Hacker News","item":"https://daily.dev/sources/hn"},{"@type":"ListItem","position":3,"name":"Building a weather data warehouse part I: Loading a trillion rows of weather data into TimescaleDB"}]}
```

