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AtScale Rockets



The OLAP engine that delivers complex analytics at scale.

How Can OLAP Work for Today's Big Data

AtScale re-invented the OLAP engine from the ground up. AtScale’s unique “just in time” approach delivers maximum speed and scalability with the computational flexibility you need to answer all your business questions.

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Drill Anywhere, For Any BI Client

Find the needle in the haystack by drilling to the atomic, raw data with AtScale’s automatic data lineage and no data movement architecture.

Cost Optimized, Graph-Based

AtScale optimizes queries, on any data platform, to automatically deliver the fastest query response time while minimizing load and improving concurrency.

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Multidimentional, Tabular
& Built for Scale

Multidimensional & Tabular

Upgrade to a modern BI platform with support for time-based calculations, hierarchies, semi-additive metrics, multi-level measures, many-to-many relationships, and more.

Built for Scale

Move beyond simple sums, averages, and counts to large scale distinct counts and quantiles using AtScale’s built-in support for HLL++ sketch sets.

Simple, Powerful Model Building
& Automated Model Creation

Simple, Powerful Model Building

Easily manipulate your cube, validate your model, and explore data in the easiest and most powerful data modeler.

Automated Model Creation

Automatically extract the business logic from your BI dashboard data models and create a unified semantic layer that works for all BI tools.

Use Case Spotlight: Create One Set of Business Logic Across Disparate BI Tools

The Challenge

Toyota had thousands of BI analysts on their IoT and Finance teams using Tableau and Power BI. As part of the move to a Cloudera data lake on Hadoop, they wanted to provide a single set of business definitions across this user constituency.

The Solution

Toyota's data modelers used the AtScale Virtual Data Warehouse's OLAP features to craft virtual cubes that could be easily accessed by analysts in Tableau and Power BI, and that could scale as data grew without the need for complex manual cube rebuilds.

Resources on OLAP for Today's Data