Damian Black, SQLstream CEO, stopped by to introduce his company, discuss a few industry trends, and introduce the company's s-Server 3.0. Here's a summary of our interesting conversation:
SQLstream has been working to help its customers manage and use real-time streams of operational data using familiar ANSI SQL rather than forcing them to learn new techniques and tools. They've also worked to make their technology enhance the use of other Big Data tools, such as Apache Hadoop.
Our discussion examined the industry in the following way:
SQLstream describes s-Server in the following way:
SQLstream s-Server 3.0 is a massively scalable, real-time Big Data management platform. Data feeds can be anywhere and in any format, including log files, sensors, networks, social media and web feeds. Real-time alerts, aggregated information and in-memory operational intelligence can be visualized immediately while streaming the information directly to external systems, applications and databases. Ultimately, you gain immediate insight into your data, enabling you to respond while it matters.
Version 3 adds increased performance, offers plug-ins allowing access to a large number of applications and tools, and makes it possible to analyze data as it arrives as if it were stored in a traditional relational database.
Organizations find it difficult to keep up with the rapidly generated data coming from their operational systems. This can include log files generated by operating systems, application frameworks, data management tools, storage systems and networks. It can also include data generated by industrial or security sensors, wireless devices, GPS data or data coming from the organization's business transactions. While tools such as Hadoop, NO-SQL and others can be useful, a fast implementation of a SQL-based database would make life easier for IT developers and analysts who are already familiar with ANSI standard SQL as a mechanism for data access and analysis.
I like the fact that this tool makes Big Data analytics available to organizations without forcing them to relearn everything and take up a different approach to data management and analysis.