Big Data Architecture

Unicage Architecture

Unicage has a distributed parallel processing cluster architecture.


Feature Hadoop Appliance Devices Unicage Architecture Description
OSS Based X X Runs under any UNIX-based OS (Linux/Free BSD)
Inexpensive Hardware X X Runs on entry-class servers
Scale Out Architecture X X Can be scaled out similar to Hadoop
Can increase processing nodes dynamically based on load
High Speed Performance X X X High-speed commands (usp Tukubai) and distributed processing
Can be used for front-end processing for legacy DB apps and Hadoop
Maintenance and Support X X Can be supported by anyone savvy in OS kernel technology
Stability X X Only uses the features of UNIX that have been stable for 40 years


Proceed Task Speed
1. Select (para-grep) Select all records starting with the text “123” from among 1 billion records 3 secs.
2. Sort (clust-qsort) Sort 1 billion random in ascending order 97 secs.
3. Sum (clust-sm2) Sum key fields in 1 billion random records 35 secs.
4. Mathematical Operations (clust-awk) Perform mathematical calculations between fields on 1 billion records 22 secs.
(clust-lcalc) Perform precision floating-point operations 67 secs.
5. Join (clust-join1) Perform a join operation on 1 billion 37 secs.
6. Complicated Operations (clust-shell) Distribute 1 billion records by key block units and perform several calculations (keys sumup, average, round literal) 17 secs.
7. Big Data Select (apli-select) Perform a matching select on 10,000 transactions (join and exclude) from among 10 billion records 4.5 secs.
8. Big Data Update (Add & Change, Delente, Sum) Apli-update Apli-delete Apli-sumup Update (add & change), delete and sum 10,000 transactions from among 10 billion records 5.5 secs
9. Big Data Search (apli-search) Search account holder data based on Rank, Gender, Geographical Region, Age Group, Length of Membership and Minimum Average Score among 10 billion records 1.2 secs.


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