Amazon Redshift + Aginity

Analyze data from a simple and fast cloud data warehouse with Aginity’s unique SQL tools.

Fast, simple, data warehousing

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Easy to configure, mange and extend, Redshift is a great platform to accelerate your analytic insights.  

  • Store, manage, and analyze petabytes of data
  • Leverage a huge library of advanced analytical functions
  • Massively parallel processing (MPP) data warehouse architecture to parallelize and distribute SQL operations

Redshift Features
We Love

A powerful data warehouse solution

  • Tight integration with S3 via Redshift Spectrum to easily query data in S3 buckets
  • Access a vast library of advanced analytical functions
  • Ease by which it powers Amazon Sagemaker machine learning models
  • ANSI SQL syntax you already know.  Based on Postgres and learning to use is a breeze

Aginity Extends Redshift

Reuse Your SQL

Save your work in an active analytics catalog so you can easily reuse your SQL rather than re-write it

Find Your Work

Easily find your previous SQL assets from your query history and analytics catalog

Feature Engineering

Develop features once for re-use across your machine learning models

Collaborate with Your Team

Share your SQL work with your teammates securely

What is an active analytics catalog?

Built with your role in mind

Use your SQL in a whole new way

– Save queries, relationships, and snippets once for reuse in SQL statements

– Find previous work in query history or your catalog

– Describe code with rich titles and descriptions help you remember why you wrote it in the first place

Easily design and maintain your data warehouse 

– Create data models and schemas 

– Analyze data across database platforms

– Reuse—don’t recode—your common SQL logic

Produce consistent reports quickly for your team

– Spend less time rewriting SQL and more time reusing it

– Define, document, and save common analytics in your personal catalog

– Efficiently re-run analysis and reports with consistent results

Spend more time training models and less time data wrangling

– Develop reusable features to train machine learning models

– Create flexible commonly used data cleansing SQL

– Use your SQL as objects to make complicated queries more simple

Case Study:
Chicago Transit Authority


At CTA, we use Amazon Redshift to consolidate our other data silos for analysis and reporting. And for our ~80 user analyst community, we have standardized on Aginity for ad-hoc analysis and insights of that Redshift data. We originally evaluated a number of Amazon-compatible SQL IDE tools, but found that Aginity offered a service that our users could take advantage of with minimal support.

Data Import Challenge

Many of our users need to quickly upload spreadsheets or files of data for analysis and while other tools offer ability to import and export data, this often requires extra fees or was found to be a cumbersome and overly-technical implementation that was a challenge for less-technical end users.

Aginity Approach 

Aginity’s wizard-driven approach makes this easy to quickly get data uploaded into S3/Redshift for ad-hoc analysis. This tool provided a set of guided steps that enable our less-technical end users to leverage it without many questions or issues.

CTA Analyst Onboarding

Because this use case is so pervasive, we have actually standardized our S3 buckets, Redshift sandboxes and IAM security so as new analysts are on-boarded and provided with Aginity, their accounts are all set up in a way that supports this ad-hoc upload-and-analyze approach.

Reuse Your Code. Empower Your Team.

Aginity Pro

Reuse your SQL. Don't recode it.

Aginity Team

Share your team's SQL.

Aginity Redshift Catalogs

Import our Redshift toolkits and getting started catalogs from Github into Aginity Pro/Team, giving instant access to hundreds of useful SQL utilities, queries and snippets. 

Active Analytic Catalog

Businesses Using Aginity with Redshift