A US-based product company that offers enterprise search & discovery platforms based on big data technologies engaged CloudScaleQA to evaluate performance of their platform and compare against other open-source platforms using industry standard TPC-H benchmarking system

Introduction:The client’s product connects with diverse enterprises and information sources and added a new SQL interface to facilitate their customers to search using familiar SQL interface. The client wanted to compare the performance of their system against Hadoop+Hive eco system using TPC-H benchmarking system for relational databases

Problem statement

  • The client wanted CloudScaleQA to build a repeatable, extensible and reliable solution to benchmark their product
  • Creating a realisable cluster for the client product and writing custom connectors to import data
  • The client’s product connects with all the diverse information sources available in an enterprise - email systems, enterprise resource planning systems, customer relationship management systems, document management systems like SharePoint and many others in to a single source

Solution and implementation

  • CloudScaleQA took a holistic approach for this benchmarking exercise by using both relational as well as non relational sources into consideration.
  • Researched TPC-H benchmarking standard, generated test data for a specific scale factor
  • Built a Hadoop Cluster, added Hive, and using Sqoop imported data from MySQL and ran the TPC-H benchmark for this system
  • Researched client’s product, built a cluster, wrote custom connectors to import data from MySQL and ran TPC-H benchmark for this system
  • Built a web based tool, to run any ad-hoc SQL queries against client’s product, Hadoop+Hive and MySQL and collect performance stats in real-time



  • CloudScaleQA approach offered the client repeatable and reliable solution to benchmark their product
  • The solution was both extensible, enabling more data sources to be added in future and scalable, wherein data for multiple load factors was supported by TPC-H
  • As a result client was also able to identify the areas of focus and was pleasantly surprised to see their product performing exceptionally well, in some cases compared to even MySQL

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