Batch-based ETL processes are only efficient when dealing with a few hours or days of data. Further limitations arise from the fact that data from disparate sources using different data models require pre-processing before being stored in the data warehouse. These limitations typically exclude the most recent data from OLAP analyses, restricting their optimum potential for informing enterprise decisions.

SQLstream Solution

SQLstream enables true real-time data warehouses. SQLstream adds new capabilities that increase scalability and keep it current while eliminating latency and downtime. SQLstream scales with data volume, offloading the data warehouse of billions of messages per day while reducing or eliminating the need for expensive database queries and batch processing.

SQLstream eliminates the need for data staging and pre-processing. SQLstream also enables testing and analysis on live data, accelerating application and query deployments, processing log files and cutting costs.

How is all this possible?

SQLstream's real-time data warehousing solutions provide a a new level of responsiveness to queries, analytics and application integration. By capturing and processing streaming data in-flight rather than static, older data stored on disk, your queries ask and answer up-to-the-minute questions with real-time precision.

While conventional ETL has difficulty accessing such data, streaming SQL enables you to bring this data into the same format as other enterprise data, combine it as needed, analyze and act on it, all in real-time.