AtScale delivers BI on Hadoop

AtScale is armed with advanced analytics capabilities for the most complex BI needs. Use your existing visualization tools to connect to and interactively query Hadoop-scale data sets

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"AtScale’s no-ETL and no-data movement approach is simply a game-changer. This application should be required for anyone who wants to do BI on Hadoop."
- Kevin Johnson, CEO, eBates

The world's first Hadoop-native, scale-out business intelligence platform

Our novel approach to Business Intelligence on Hadoop accesses data as it has been written, directly on the Hadoop cluster, instead of taking it out of the Hadoop cluster and persisting it in a different system for consumption. The results of this type of 'query-in-place' integration are significant: BI agility is significantly enhanced. Operational cost and complexity are reduced. Data 'freshness' is dramatically increased.

Use your favorite visualization tools, at scale

The AtScale Intelligence Platform supports Business Intelligence on Hadoop by providing native support and integration for the most widely-adopted BI and visualization tools in today’s enterprises - tools like Tableau, Qlik, Spotfire, and Microsoft Excel. AtScale dynamic cubes integrate nicely with their existing BI tools while also providing a layer of governance to ensure standardization of business logic across big data consumers.

Smart aggregations enable interactive Business Intelligence on Hadoop

The AtScale engine has built-in intelligence that uses dynamic cube definitions and user query patterns to create smart aggregations that deliver interactive query performance on Hadoop data. The AtScale engine supports robust set of rules and algorithms that keep cubes up to date while preserving a performance profile that supports interactive analysis and analytics.


BI on Hadoop. Any Hadoop Tools.

AtScale supports all the major Hadoop tools - Cloudera, Hortonworks, MapR, and Microsoft Azure HDInsight. Additionally, AtScale can work natively with the top SQL-on-Hadoop engines - Impala, SparkSQL, and Hive-Tez.