Google Research

Tenzing A SQL Implementation On The MapReduce Framework

  • Biswapesh Chattopadhyay
  • Liang Lin
  • Weiran Liu
  • Sagar Mittal
  • Prathyusha Aragonda
  • Vera Lychagina
  • Younghee Kwon
  • Michael Wong
Proceedings of VLDB, VLDB Endowment (2011), pp. 1318-1327


Tenzing is a query engine built on top of MapReduce for ad hoc analysis of Google data. Tenzing supports a mostly complete SQL implementation (with several extensions) combined with several key characteristics such as heterogeneity, high performance, scalability, reliability, metadata awareness, low latency, support for columnar storage and structured data, and easy extensibility. Tenzing is currently used internally at Google by 1000+ employees and serves 10000+ queries per day over 1.5 petabytes of compressed data. In this paper, we describe the architecture and implementation of Tenzing, and present benchmarks of typical analytical queries.

Learn more about how we do research

We maintain a portfolio of research projects, providing individuals and teams the freedom to emphasize specific types of work