White Paper
Powering SQL on Hadoop: Evaluation of TPC-DS Query Benchmark Using Hadoop
Date: 03/14/2017 Length: 5 pages Cost: $99.00

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EMA big data research conducted regularly from 2012-2016 shows that organizations implementing Hadoop as part of their data management environments are moving from simple exploratory use cases to complex workload-driven analytics use cases. These organizations are working for the implementation of mission-critical business goals and workloads in environments that utilize Hadoop. According to EMA panel respondents, the most commonly implemented use cases are market basket analysis, social brand management analysis, fraud analysis and risk assessment, geospatial grouping, and relationship analysis. All of these projects require access to speed of response and many different groups across the organization.

These advanced workloads are SQL-intensive, requiring a full range of current ANSI SQL query support--not just a subset. In addition, many workloads must support the type of low-latency response business stakeholders require. Finally, these platforms need to support a level of concurrent users who will use these environments. When analytical applications gain adoption, their use becomes widespread and the underlying data management platform needs to support users while providing an acceptable level of performance.

An effective SQL on Hadoop environment must support advanced ANSI SQL versions such as SQL99 and SQL2003 to effectively maintain analytical and business intelligence query workloads. This is essential for business users who are loath to make adjustments from the queries used currently. Full SQL support is also critical when an enterprise plans to utilize data analysis and data visualization tools which generate their own SQL in ways that the data consumer and IT technologies do not fully control.

John Myers, Former EMA Analyst


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