Big data requires ever more powerful means to process and analyze growing stores of data, being collected at more rapid rates, and with increasing diversity in the types of data being soughtboth structured and unstructured. In-memory computings rapid rise in the marketplace has the big data community on alert.

Download this illuminating white paper about what YARN really means to the world of big data management.

Most data masking products can create masked data copies but not distribute or update them, resulting in projects that fail to live up to expectations. Learn why Delphixs Agile Masking solution is the only product that solves both masked data creation and delivery challenges.

This white paper examines key approaches to application modernization and evolution for certain IBM mainframe applications with long life spans. It discusses the challenges of legacy applications and the available modernization approaches to handle these challenges. The paper also analyzes in some depth specific approaches that keep application logic largely intact or allow it to evolve incrementally and productively.

Download this whitepaper to learn the results of this latest exploration of the emerging world of in-memory database technologies.

This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.

For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.

DB2 BLU By Other Databases And More Wayne Kernochan, Infostructure Associates September 2013 Analyst Wayne Kernochan of Infostructure Associates documents the analytics speed-up capability of DB2 with BLU Acceleration and explains how DB2 BLU compares with competitors. His conclusion after reviewing test results? ""Not surprisingly, the results verified a consistent, roughly order-of-magnitude speedup using BLU Acceleration, against DB2 pre-BLU and against some obvious competitors ..."". What is his advice to readers about DB2 BLU? ""... if your upcoming database needs are analytics/BI/reporting-related, why would you not use BLU Acceleration for them? In other words, what are you waiting for?

Big Data is not a new probl