# From multi-day latency to near real-time insights: Figma's data pipeline upgrade

DevFeed: [From multi-day latency to near real-time insights: Figma's data pipeline upgrade](<https://devfeed.tech/articles/from-multi-day-latency-to-near-real-time-insights-figma-s-data-pipeline-upgrade-9710.md>)

Original publisher: [Read original article](<https://www.figma.com/blog/figmas-data-pipeline-upgrade/>)

Author: Yichao Zhao

Published: 2025-05-29T00:00:00Z

Content type: article

Language: en

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

Topics: [Figma](<https://devfeed.tech/topics/figma.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [real-time](<https://devfeed.tech/topics/real-time.md>), [data](<https://devfeed.tech/topics/data.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>)

Tags: [architecture](<https://devfeed.tech/tags/architecture.md>), [data](<https://devfeed.tech/tags/data.md>), [database](<https://devfeed.tech/tags/database.md>), [figma](<https://devfeed.tech/tags/figma.md>), [insights](<https://devfeed.tech/tags/insights.md>), [latency](<https://devfeed.tech/tags/latency.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [s3](<https://devfeed.tech/tags/s3.md>), [sync](<https://devfeed.tech/tags/sync.md>)

## AI overview

Figma describes rebuilding its legacy data synchronization pipeline after rapid growth caused daily exports to take hours or days. The original system used a daily cron job to query online relational databases, upload results to Amazon S3, and import them into Snowflake. The article introduces an incremental synchronization approach intended to reduce latency to near real time and support scalable analytical insights.

## Source excerpt

After an exponential growth in users and data, daily synchronization tasks started taking hours or even days to complete. Here's how rebuilding a data pipeline reduced latency to near real-time.