By Rich Ptak
It’s no
secret that the action today is in Big Data and the associated Analytics! Whether for
business, retail, education, government, medical, media, whatever, the focus is
on data! Lots of it! Coming from every direction in every conceivable source and
format. It is structured, unstructured, transactional, audio and visual flowing
from IoT, mobile, social, production…to the tune of some 2.5 quintillion new
bytes generated every single day.
IT is tasked
with processing this raw data into the insights, wisdom, knowledge that result
in new services or deliver solutions to previously impenetrable mysteries. The
ultimate goal is to deliver benefits and provide value to users, clients and
customers. Processing large amounts of data has been computing’s forte since
their inception. BUT now the processing of data and generating results is
immensely more complicated and must be delivered more quickly and economically
than ever before.
IBM’s Power8 was specifically designed as a
Big Data server with
industry leading memory bandwidth, thread density, and cache architecture. It
has the analytics tools[1],
operating systems[2],
databases[3]
to be the System of Insight equipped to deal with the software,
performance and management challenges of Big Data analysis, integration and
governance.
And, in
discussions with users, we’ve seen that it delivers. See our blogs about
customer[4]
success at dealing with Big Data challenges using Power8 systems. Whether
the goal is near real-time response (1.5 microsecond Algo-Logic’s Tick-to-Trade);
significant cost savings with improved performance (IBM Platinum Partner Redis
Labs processes more REDIS-NoSQL transactions with faster response times with
fewer CAPI-Power8 servers); or TalkTalk[5], a UK communications
service provider, updating their network and improving the service to their
customers by switching to Power-CAPI powered servers.
No
industry-standard benchmark existed for Apache
Spark[6]
until IBM developed the SparkBench benchmark suite. The first version includes
10 benchmarks covering four use cases: Machine Learning, Graph, SQL and
Streaming Spark. The results are that a wide
variety of Spark workloads consistently run 2x faster on POWER8 than competitor
platforms. (FACT: POWER8 with 24
processor cores runs 37% faster than Haswell with 36 processor
cores.) You can get SparkBench details and results here[7]. And, if you want to make sure that the SparkBench is the REAL thing, it
is available to the public here[8]. IBM recently announced LinuxONE[9] for the mainframe world, we expect more interesting information in the October
5th webcast on new capabilities and products. We’ve registered and suggest that
you do so also at: http://tinyurl.com/nctlofd.
[1]
Hadoop,
Big Insights, DB2BLU and Spark
[2]
Red Hat, SuSE and Ubuntu
[3] Oracle, DB2LUW, MariaDB, MongoDB,
PostgreSQL
[6] An in-memory distributed compute
engine to complete analysis on large-scale data sets up to 100X faster than
current technologies. More info on Apache Spark here: http://tinyurl.com/nta8zvz
[1]
Hadoop,
Big Insights, DB2BLU and Spark
[2]
Red Hat, SuSE and Ubuntu
[3] Oracle, DB2LUW, MariaDB, MongoDB,
PostgreSQL
[6] An in-memory distributed compute
engine to complete analysis on large-scale data sets up to 100X faster than
current technologies. More info on Apache Spark here: http://tinyurl.com/nta8zvz