It’s well known that if you go noSQL, you lose the relational set operations of a traditional RDBMS. It then falls to the application layer to perform the set joins as needed, or to create a hybrid noSQL/RDBMS environment, but as anyone in big data can attest, it’s just not scalable. It’s possibly the largest problem facing big data.
Unity works between your data source and destination in a seamless, easy-to-use way. Most implementations require very little effort to reap immediate benefits at scale.
Leverage your existing noSQL solution, or spin up a custom Unity cluster to keep the data separated. You're in full control. Or push your data to our cloud service and let us do all the work.
Unity's patent pending technology solves the relational problem allowing complex, set-based operations to occur on unstructured data sets in near-real-time. Scale like noSQL, analyze like SQL.
Three different threat feeds provide known CnC, Ransomware, and other Blacklisted IPs. How can we detect these bad IPs in syslog and netflow data within one second?
(383 trillion) operations per second
are required to search every field in every document against every other field in every other document.
| Document Multiplier||1X||2X||5X|
Increasing Data Lakes:
Assumptions are 1,000,000 netflow documents per day with 96 fields, 125,000 syslog documents with 173 fields, and three threat feeds of approximately 33,000 documents per day with an average of 33 fields per document. Additional data lakes are estimated as 250,000 documents per day with 25 fields per document. Operation and search numbers represent maximum operations at the end of the day. The number of operations and searches would likely fluctuate throughout the day in actual practice. Operation and search numbers are averaged across the day assuming a uniform distribution of streaming data input.