# Introducing Analytics Buckets

DevFeed: [Introducing Analytics Buckets](<https://devfeed.tech/articles/introducing-analytics-buckets-405.md>)

Original publisher: [Read original article](<https://supabase.com/blog/introducing-analytics-buckets>)

Author: Fabrizio Fenoglio

Published: 2025-12-02T07:00:00Z

Content type: release

Language: en

Sources: [Supabase Blog](<https://devfeed.tech/sources/supabase-blog.md>)

Topics: [Apache Iceberg](<https://devfeed.tech/topics/apache-iceberg.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>)

Tags: [amazon-s3](<https://devfeed.tech/tags/amazon-s3.md>), [analytics](<https://devfeed.tech/tags/analytics.md>), [apache-iceberg](<https://devfeed.tech/tags/apache-iceberg.md>), [parquet](<https://devfeed.tech/tags/parquet.md>), [postgres](<https://devfeed.tech/tags/postgres.md>), [s3](<https://devfeed.tech/tags/s3.md>), [scale](<https://devfeed.tech/tags/scale.md>), [schema-evolution](<https://devfeed.tech/tags/schema-evolution.md>), [storage](<https://devfeed.tech/tags/storage.md>), [time-series](<https://devfeed.tech/tags/time-series.md>)

## AI overview

Supabase introduces Analytics Buckets for storing large analytical datasets in Supabase Storage. The service uses Apache Iceberg, Amazon S3, and columnar Parquet files, while Postgres remains suited to transactional application data.

## Source excerpt

Use Analytics Buckets to store huge datasets in Supabase Storage with Apache Iceberg and columnar Parquet format, optimized for analytical workloads.