Director of Power Systems
Three must-have capabilities for today’s warehouse environments
Are you seeing an explosion in data volume while at the same time experiencing higher demands for big data analytics? Are you now required to provide insight and agility to generate new opportunities while also attempting to contain costs and satisfy your customers? You know that big data analytics are pervasive, and that analytics benefit from performance gains. And, you might have already experienced the benefits of better decision making thru big data analytics. But what if you could make business decisions faster – 82 times faster – while reducing IT spending?1
IBM DB2 BLU provides significant performance improvements to big data analytics, like Cognos, and POWER8 and DB2 BLU provide the highest performing analytics today, regardless of the analytic methods being used. DB2 with BLU Acceleration on IBM Power Systems with POWER8, the first processor designed for big data and built with open innovation, can help you maximize your analytics investment. Power Systems is the only platform that supports both Linux and UNIX environments for in-memory database processing.
Some additional benefits include:
- Handles rapidly growing volumes of big data, cost-effectively.
- Accelerates results and simplify the process of extracting value from your data.
- Minimizes demands on your IT staff while maximizing return on investment.
- Transforms the way big data analytics solutions are deployed in your environment.
IBM customers using DB2 with BLU Acceleration on Power Systems are seeing remarkable results.
Some examples include:
- A leading health insurance company experiences 1000X faster business insights.2
- A recreational goods company experiences 140X faster queries.2
- A large bottling company experiences 10X storage space savings.2
Learn more about our big data solutions.
1. Based on IBM internal tests as of April 17, 2014 comparing IBM DB2 with BLU Acceleration on Power with a comparably tuned competitor row store database server on x86 executing a materially identical 2.6 TB BI workload in a controlled laboratory environment. Test measured 60 concurrent user report throughput executing identical IBM Cognos® report workloads. Report per hour (RPH) metric calculated for each category of reports as total completed reports/hours to complete all reports in the category. Competitor configuration: HP ProLiant DL380p, 24 cores, 256 GB RAM, competitor row-store database, SuSE Linux 11SP3 (database) and HP ProLiant DL380p, 16 cores, 384 GB RAM, Cognos 10.2.1.1, SuSE Linux 11SP3 (Cognos). IBM configuration: IBM Power System S824, 24 cores, 256 GB RAM, DB2 10.5, IBM AIX® 7.1 TL2 (database) and IBM Power System S822L, 16 of 20 cores activated, 384 GB RAM, Cognos 10.2.1.1, SuSE Linux 11SP3 (Cognos). Results may not be typical and will vary based on actual workload, configuration, applications, queries and other variables in a production environment.
2. Client-reported testing results in DB2 10.5 early release program. Individual results will vary depending on individual workloads, configurations and conditions, including table size and content.