Microsoft SQL Server Analysis (SSAS) is Microsoft’s solution for delivering Online Analytical Processing (OLAP) solutions. As a multi-dimensional interface, OLAP is preferred by business users over writing SQL queries, delivers “speed of thought” queries and frees users from manual data engineering tasks. However, there are some major challenges using SSAS to scale and modernize your analytics initiatives. SSAS doesn’t integrate well with many of the new technologies and modern data practices and inhibits the transition to cloud-based analytics beyond Microsoft Azure. SSAS also has troubles scaling with today data sizes and requires data movement and duplication.
The AtScale Difference: The Best of SSAS Without the Baggage
With AtScale, you can scale up and modernize your business intelligence (BI) infrastructure while keeping SSAS’s strong multidimensional functionality. Instead of moving data, AtScale leverages the underlying data platforms as the primary engines for analytics. So wherever the data exists Hadoop, a cloud data warehouse, or an on premises data warehouse, it can stay there. AtScale provides an analytics semantic layer that automatically manages performance and makes any data platform perform like a high speed OLAP engine. AtScale joins data from multiple data platforms to deliver one single source of truth for BI and analytics tools. AtScale eliminates the inherent scaling issues with SSAS MD/Tabular and eliminates cube builds by replacing SSAS’s physical cube with a virtual cube. Moreover, AtScale is the only solution to provide a live DAX interface for Power BI to deliver the superior performance for cloud data warehouses like Snowflake, Google BigQuery and Amazon Redshift.
AtScale delivers fast, multi-dimensional, secured and governed data access without data movement. Only AtScale virtualizes data platforms, combining BI with artificial intelligence (AI) with a universal semantic layer, to provide one single view of data.
AtScale advantages over SSAS include:
- Works directly on any data platform – Hadoop, Snowflake, BigQuery, Redshift, Azure Synapse SQL, Postgres and more – without the need to extract data and build a physical cube-like SSAS
- Scales with your data platform rather than requiring you to provision a separate environment for hosting your cubes like SSAS
- Handles any amount of data because AtScale doesn’t require that you precompute every possible combination of dimensions and measures
- Supports multidimensional models (SSAS MD) so there’s no need to port your cubes to tabular models
- Supports Tableau and Looker via a JDBC SQL interface
- Doesn’t require ETL as AtScale models cubes virtually without data engineering
- Supports business intelligence and data science workloads via AtScale’s AI-Linktm
- Handles data in different data stores and locations via data virtualization
- Can be deployed in any Linux ecosystem either on-premise or in the cloud