Selecting the Right Data Warehouse for Analytics

This ebook will help you understand six key elements to consider when selecting a data warehouse for analytics. It will also dive into use cases best suited for top data warehouse providers.

How it works

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Store and standardize your data in one place you trust

Test your implementation and weed out bad data

Schema Control
See what events and traits you’ve sent, and set rules for where data flows

Collect data from every platform and load it easily into Segment

Web, Mobile, and Server-side Libraries
Choose from Javascript, iOS, Android, Ruby, Python, and more

Cloud Apps
Connect cloud platforms like Salesforce, Stripe, Facebook, and more


Send data to hundreds of tools and data warehouses

Send Data Anywhere
Explore our catalog of tools for analytics, email, and more

Data Warehousing
Schematize and load your data into a cloud data warehouse like Redshift, BigQuery, and Postgres



Inside you'll find:

Why a data warehouse is absolutely essential to analytics at scale

The six key elements to consider when evaluating a data warehouse

Uses cases that are best suited for different types of data warehouses

A no-nonsense vendor selection breakdown for Redshift, Snowflake, BigQuery, Db2Warehouse, and Postgres