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Introducing Supabase Pipelines. Your app runs on Postgres, but your analytics usually live somewhere else, like BigQuery. Pipelines keeps that data in sync for you in near real time, with no pipeline to build or maintain.

Supabase

209,469 subscribers

63,426 次观看 • 3 个月前 •via X (Twitter)

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21 条评论

Supabase 的头像

Supabase3 个月前

It's built on Postgres logical replication, powered by our open-source engine, Supabase ETL. It runs the initial sync, replicates every insert, update, delete, and truncate, and keeps your destination schema in sync as your Postgres schema changes. BigQuery is live now. ClickHouse, Snowflake, and DuckLake are available on request. Read more:

Supabase 的头像

Supabase3 个月前

Tune into our weekly livestream on Mondays at 23:00 UTC to ask questions and talk about Supabase Pipelines.

Mojeeb | Arcapush.com 的头像

Mojeeb | Arcapush.com3 个月前

amazing! i’ll set this up, right away.

Tech PlusX 的头像

Tech PlusX3 个月前

👀👀

Hixon 的头像

Hixon3 个月前

Love anything Supabase does

Jaya Nayak 的头像

Jaya Nayak3 个月前

No more wasting engineering hours building custom data pipelines.

Layerbase 的头像

Layerbase3 个月前

Clickhouse on Layerbase has been a hit. Surprised it took this long

Samian 的头像

Samian3 个月前

so you're telling me my bigquery pipeline built on a cron job and a prayer was unnecessary this whole time

AI Mastery Guide 的头像

AI Mastery Guide3 个月前

Keeping Postgres and BigQuery in sync automatically saves so much hassle

Sebastian Buzdugan 的头像

Sebastian Buzdugan3 个月前

near real time breaks first on schema drift not raw replication speed

skellertor 的头像

skellertor3 个月前

Glad I was forced to use you for a project. Never looking back now

Marco 的头像

Marco3 个月前

Right now im using GCP DataStream for this. Is this in any way better, faster or cheaper?

Hussain Fakhruddin 的头像

Hussain Fakhruddin3 个月前

No pipeline to build or maintain is the real win.

Carmelo schepis 的头像

Carmelo schepis3 个月前

why sync when you could just not

Mathieu Kessler 的头像

Mathieu Kessler3 个月前

No pipeline to build or maintain is the real win.

Fabio Lauria 的头像

Fabio Lauria3 个月前

Most teams waste weeks shuffling data between systems instead of analyzing it. The real bottleneck isn't the pipeline—it's converting synced data into actionable decisions quickly enough to drive impact. I focus on delivering insights in minutes, not days waiting for analytics teams to surface them 📊

Guru Meditation 的头像

Guru Meditation3 个月前

Is that similar to ClickPipes?

Camaleón Raro 的头像

Camaleón Raro3 个月前

real-time pipelines without building one is the actual unlock. most teams i know spend 60% of analytics eng time on the sync layer the failure mode nobody talks about: schema drift between postgres and bigquery. thats where every pipeline I've seen buckle after 3-4 months

MixRoute AI 的头像

MixRoute AI3 个月前

Love to see any new features Supabase adds.

Emile Kratiroff 的头像

Emile Kratiroff3 个月前

No app big enough to have analytics on big query runs on supabase

Valenciana 的头像

Valenciana3 个月前

@grok what does this mean for my backend in simple terms

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