Big Data Analytics
Management of IT big data
Lakeside Software is the leading provider of "big data" analytics for IT professionals.
Lakeside's SysTrack products provide the ability to store, manage, manipulate, analyze, aggregate,
combine, integrate and visualize massive structured and unstructured IT infrastructure data.
This opens the opportunity for insights into the use and deployment of IT infrastructure, promotes IT agility,
and answers questions that were previously considered beyond your reach.
The definitive patents on big data management
Key to Lakeside's ability to effectively manage big data without creating excessive network traffic is its
unique and massively scalable DataMine™ distributed relational database architecture.
Lakeside holds patents #6,978,265 and #7,865,499 which ensure SysTrack is the only tool to leverage
distributed systems management information on an enterprise scale, properly dealing with the
realities of mobility, scale and part-time connectivity.
Designed for big data
Designed for scalability, mobility and minimal performance impact, SysTrack employs on each desktop or server a small,
non-intrusive and easily removed agent. This agent uses minimal resources and contains no kernel components
that could compromise system integrity. The total network traffic SysTrack
produces over an entire day for a typical endpoint is less than 100 kilobytes.
SysTrack is suitable for extreme data volume. At one customer installation, SysTrack is storing approximately
35 samples per second on 300,000 clients. That's more than 10,000,000 samples/second saved for later use.
Sampling and statistical analysis is an order of magnitude faster, with more than 100,000,000 samples/second collected and analyzed.
And SysTrack isn't just a consumer; it produces high value data, synthesizing critical behavior, performance,
resource and interation data into a usable format. It's not just a log scanner or a perfmon tool. It's far more.
You won't find this kind of information in your event log.
How SysTrack Works
Big Data for End User Computing
End User Computing Success Platform