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The world’s most innovative companies choose Hightouch as their Composable CDP

Spotify.
Warner Music Group.
PetSmart.
WeightWatchers.
Ramp.
Calendly.
GitLab.
Grammarly.
Spotify.
Betterment.
Warner Music Group.
PetSmart.
Tripadvisor.
GameStop.
Cars.com.
WeightWatchers.
Iterable.
Ramp.
Plaid.
Calendly.
GitLab.
Malwarebytes.
Greenhouse.
Grammarly.

Get data out of Redshift. Fast.

You've spent time getting data into Redshift, modeling it for analytics, and paying to store it. Why do that again with a traditional CDP? With Hightouch, you can activate your Redshift data in less than 5 minutes. You no longer have to worry about storing your data with a 3rd party, complex CDP implementations, or having multiple data silos.

Read our Redshift documentation

What methods can I use to model my Redshift data?

  • dbt model selector

    Semi-opaque, open dropdown with three example dbt model names such as 'dbt.model.name.1'.

    Sync directly with your dbt models saved in a git repository.

  • Looker

    Semi-opaque open dropdown with three example Look names such as 'Look 1'.

    Query using Looks. Hightouch turns your look into SQL and will pull from your source.

  • SQL editor

    SQL editor.

    Create and Edit SQL from your browser. Hightouch supports SQL native to Redshift.

  • Sigma model

    Semi-opaque open dropdown with three example workbook names such as 'Workbook 1'.

    Hightouch converts your Sigma workbook element into a SQL query that runs directly on Redshift.

  • Table selector

    Semi-opaque open dropdown with three example table names such as 'schema.table.name.1'.

    Select available tables and sheets from Redshift and sync using existing views without having to write SQL.

  • Customer Studio

    Visual query builder reading 'All rows that...' with a button labeled 'select a property'.

    For less technical users, pass traits and audiences from Redshift using our visual segmentation builder.

All 200+ Redshift integrations

Redshift to Acoustic
Chaotic graph of interconnected nodes representing data warehouses, data, and business tools.

Before Hightouch

  • Inconsistent and inaccurate data
  • Laborious and expensive
  • Brittle and inflexible
Clean and easily readable graph of data moving from a warehouse node, to Hightouch, to business tools.

After Hightouch

  • Consistent and accurate
  • Observable and governed
  • Scalable and flexible