--- title: Transforming Music Data Management: How Polars Redefined... description: Vydia, a music technology platform, replaced Ruby's built-in classes with the Polars data processing library (via its community-maintained Ruby interface) to... canonical: https://daily.dev/posts/transforming-music-data-management-how-polars-redefined-csv-processing-at-vydia-x5i7gfpbx twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Transforming Music Data Management: How Polars Redefined CSV Processing at Vydia | daily.dev og:description: Vydia, a music technology platform, replaced Ruby's built-in classes with the Polars data processing library (via its community-maintained Ruby interface) to... og:url: https://daily.dev/posts/transforming-music-data-management-how-polars-redefined-csv-processing-at-vydia-x5i7gfpbx og:image: https://api.daily.dev/og/posts/X5I7GFPBX.png og:image:alt: Transforming Music Data Management: How Polars Redefined CSV Processing at Vydia 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. # Transforming Music Data Management: How Polars Redefined CSV Processing at Vydia **[Polars Blog](https://daily.dev/sources/polars)** · 5 min read · 0 upvotes · 0 comments ## Summary Vydia, a music technology platform, replaced Ruby's built-in classes with the Polars data processing library (via its community-maintained Ruby interface) to handle rapidly growing CSV ingestion volumes—now averaging around 5 million rows per file and over half a billion rows monthly. After experimenting with Polars' in-memory API, lazy API, and batched CSV reader following a RubyConf talk, the team found batched processing delivered the biggest speed and memory gains, cutting processing times from hours (or days) to minutes and eliminating frequent Kubernetes pod crashes caused by memory overload. The switch also enabled faster client payments and encouraged broader Polars adoption across product and data engineering teams at the company. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How much faster is Polars compared to Ruby's built-in classes for processing large CSV files? Polars reduced CSV processing at Vydia from hours or even days down to minutes. Vydia's royalty ingestion platform, built in Ruby, was processing files averaging around 5 million rows each, over half a billion rows monthly, and refactoring the Ruby code itself only shaved a few hours off 20+ hour running workers, whereas switching to Polars' batched CSV reader delivered dramatically better speed and memory efficiency. _See how other teams benchmark data-processing library switches like this one on daily.dev._ ### Is there a Ruby interface for the Polars dataframe library? Yes, a community-maintained Ruby interface for Polars exists, wrapping the Rust-based Polars engine (which also has official Python, NodeJS, and R interfaces). Vydia used this Ruby interface, experimenting with its in-memory API, lazy API, and batched CSV reader, and found the batched CSV reader approach gave the best combination of speed and memory efficiency for large file processing. _Developers evaluating dataframe libraries across languages can follow real adoption stories like this on daily.dev._ ### Why does row-wise CSV processing in Ruby cause memory and performance problems at scale? Row-wise processing forces transformations and validations to run one record at a time even when batching is used, which is slow and memory intensive. At Vydia this caused Kubernetes pods to crash from memory overload when handling large CSV files; switching to Polars' columnar, bulk operations combined with lazy evaluation and streaming avoided loading excessive data into memory at once. _Teams debugging memory crashes in data pipelines can track columnar-processing patterns like this on daily.dev._ ## Similar posts on daily.dev - [Crunching data? 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Pandas Didn’t Stand a Chance.](https://daily.dev/posts/i-rewrote-a-real-data-workflow-in-polars-pandas-didn-t-stand-a-chance--dpixpj7fx) · Towards Data Science · 0 upvotes · 0 comments - [Decathlon Switches to Polars to Optimize Data Pipelines and Infrastructure Costs](https://daily.dev/posts/decathlon-switches-to-polars-to-optimize-data-pipelines-and-infrastructure-costs-5gcd7b1tn) · InfoQ · 70 upvotes · 0 comments - [How to Use the Polars Library in Python for Data Analysis](https://daily.dev/posts/how-to-use-the-polars-library-in-python-for-data-analysis-stzxazhnq) · freeCodeCamp · 3 upvotes · 0 comments --- Tags: [#postgresql](https://daily.dev/tags/postgresql), [#ruby](https://daily.dev/tags/ruby), [#data-processing](https://daily.dev/tags/data-processing), [#polars](https://daily.dev/tags/polars) [View this post on daily.dev](https://daily.dev/posts/transforming-music-data-management-how-polars-redefined-csv-processing-at-vydia-x5i7gfpbx) ```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":"Transforming Music Data Management: How Polars Redefined CSV Processing at Vydia","url":"https://daily.dev/posts/transforming-music-data-management-how-polars-redefined-csv-processing-at-vydia-x5i7gfpbx","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/transforming-music-data-management-how-polars-redefined-csv-processing-at-vydia-x5i7gfpbx"},"datePublished":"2026-08-16T08:53:17.419Z","dateModified":"2026-08-16T08:55:40.295Z","description":"Vydia, a music technology platform, replaced Ruby's built-in classes with the Polars data processing library (via its community-maintained Ruby interface) to...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/5434e7bec80a8efdf8c46b2f6f76f432?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/5434e7bec80a8efdf8c46b2f6f76f432?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Polars Blog","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":"Polars Blog","logo":"https://media.daily.dev/image/upload/s--xo60W3UW--/c_limit,w_256/f_auto,q_auto/v1786870390/logos/polars?_a=BAMAMicg0","url":"https://daily.dev/sources/polars"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/transforming-music-data-management-how-polars-redefined-csv-processing-at-vydia-x5i7gfpbx","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"postgresql,ruby,data-processing,polars","timeRequired":"PT5M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Polars Blog","item":"https://daily.dev/sources/polars"},{"@type":"ListItem","position":3,"name":"Transforming Music Data Management: How Polars Redefined CSV Processing at Vydia"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/transforming-music-data-management-how-polars-redefined-csv-processing-at-vydia-x5i7gfpbx#faq","mainEntity":[{"@type":"Question","name":"How much faster is Polars compared to Ruby's built-in classes for processing large CSV files?","acceptedAnswer":{"@type":"Answer","text":"Polars reduced CSV processing at Vydia from hours or even days down to minutes. 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