The ability to harness the power, agility and scalability of the cloud for data-intensive applications, like Internet–of-Things (IoT)-driven applications that analyze real-time streams of fast data, is critical to business success in today's data-driven economy. This year's benchmark effort analyzed the performance of Amazon Web Services (AWS), Google Cloud Platform, IBM SoftLayer bare metal, IBM SoftLayer virtual machines and Microsoft Azure using the Yahoo Cloud Serving Benchmark (YCSB), an open-source specification and popular cloud performance benchmark.
Cloud Performance Benchmark Results
Looking at YCSB operations per second performed by the six-server cluster tested on each cloud platform, and the cost per hour of these clusters, key takeaways include:
- IBM SoftLayer bare metal has more than 2.6 times the performance (1,543,000 operations/second for SoftLayer compared to 585,000 operations/second for AWS) and nearly three times the price performance of AWS (4.630 billion operations/dollar for SoftLayer compared to 1.608 billion operations/dollar for AWS)
- With 1,038,586 operations/second, Google Cloud Platform has nearly twice the performance and three times the price performance (3.338 billion operations/dollar) of AWS
- Microsoft Azure delivers solid performance at 902,017 operations/second, but the lowest price performance at 0.415 billion operations/dollar due to limited configuration options for the benchmark
For a full description and all the details, see the ACME Benchmarking write up at: http://bit.ly/1Mxgp4F
Based on the results of the benchmarking analysis, bare metal deployments excel in performance and price/performance compared to the more full-service cloud platforms. However, when looking at strictly cloud-based platform-as-as-service (PaaS) providers, Google is a step ahead of both Amazon and Microsoft Azure on both performance and price/performance.
The cloud remains a cost-effective option for exploring the potential of data-intensive and IoT-driven applications with minimal risk. For example, Evans Data Corporation recently reported that IoT developers are three times more likely than their non-IoT counterparts to use the cloud as a development environment. Cloud platforms offer significant differences in performance speed and price/performance, requiring users to evaluate vendors carefully based on the users' specific needs. By using the cloud to provide a faster time-to-value for fast data-powered applications, organizations can more effectively keep pace with the speed of today's business.
"VoltDB is being deployed to power fast data-driven applications in the cloud, combining streaming analytics with transactions so you can act at the rate that you learn," said Bruce Reading, chief executive officer and president of, VoltDB. "These results showcase the tremendous performance, price and scalability benefits of today's cloud offerings for developing and deploying fast data applications. As organizations look to meet their fast data application demands in the cloud, VoltDB is the only modern in-memory OLTP platform that offers the ability to use streaming analytics in user and operational interactions, enabling new levels of application functionality and performance."
To see the VoltDB perspective on the benchmark, please visit our blog.
VoltDB recently released Version 5.7 of its in-memory database, which is available for download at: http://voltdb.com/download/software.
About VoltDB
VoltDB's in-memory SQL database combines streaming analytics with transaction processing in a single, horizontal scale-out platform. Customers use VoltDB to build applications that process streaming data the instant it arrives to make immediate, per-event, context-aware decisions. By delivering real-time in-transaction analytics that always produce correct results, VoltDB enables businesses to capture economic value and develop new revenue opportunities in the mobile, financial services, IoT, energy, advertising, and security industries. VoltDB is privately held with offices in Bedford, Massachusetts, and Santa Clara, California.
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SOURCE VoltDB
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