SSAS vs. Apache Kylin

Apache Kylin

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What is SSAS?

When implemented as an on-premises server, SQL Server Analysis Services offers extensive support for multiple model types, such as tabular models at different compatibility levels depending on the version, multidimensional models, data mining features, and Power Pivot functionalities for SharePoint. The typical implementation process consists of establishing a SQL Server Analysis Services instance, creating either a tabular or multidimensional data model, deploying this model as a database to the server instance, processing it to fill it with data, and setting up user permissions to enable data access. After this setup is finalized, client applications compatible with Analysis Services can readily access the data model as a source. These data models often aggregate information from external systems, primarily retrieving data from data warehouses that utilize SQL Server or Oracle relational database engines; however, tabular models are also capable of connecting to various other data sources. This flexibility and range of capabilities underscore the strength of SQL Server Analysis Services as a formidable resource for analytics and business intelligence, allowing organizations to derive meaningful insights from their data. Ultimately, such robust functionality positions SQL Server Analysis Services as an essential component for enterprises aiming to enhance their analytical capabilities.

What is Apache Kylin?

Apache Kylin™ is an open-source, distributed Analytical Data Warehouse designed specifically for Big Data, offering robust OLAP (Online Analytical Processing) capabilities that align with the demands of the modern data ecosystem. By advancing multi-dimensional cube structures and utilizing precalculation methods rooted in Hadoop and Spark, Kylin achieves an impressive query response time that remains stable even as data quantities increase. This forward-thinking strategy transforms query times from several minutes down to just milliseconds, thus revitalizing the potential for efficient online analytics within big data environments. Capable of handling over 10 billion rows in under a second, Kylin effectively removes the extensive delays that have historically plagued report generation crucial for prompt decision-making processes. Furthermore, its ability to effortlessly connect Hadoop data with various Business Intelligence tools like Tableau, PowerBI/Excel, MSTR, QlikSense, Hue, and SuperSet greatly enhances the speed and efficiency of Business Intelligence on Hadoop. With its comprehensive support for ANSI SQL on Hadoop/Spark, Kylin also embraces a wide array of ANSI SQL query functions, making it versatile for different analytical needs. Its architecture is meticulously crafted to support thousands of interactive queries simultaneously, ensuring that resource usage per query is kept to a minimum while still delivering outstanding performance. This level of efficiency not only streamlines the analytics process but also empowers organizations to exploit big data insights more effectively than previously possible, leading to smarter and faster business decisions. Ultimately, Kylin's capabilities position it as a pivotal tool for enterprises aiming to harness the full potential of their data.