NoSQL databases, such as Apache Cassandra, are often used in operational applications. However, a new breed of databases, such as Volt Active Data, are revolutionizing the fast data landscape. Volt Active Data is an in-memory NewSQL transactional database for fast data applications, currently in use by major telcos, financial services, and many other markets.
To display the competitiveness in performance between Volt Active Data and Cassandra, two separate benchmarks were compared. The first benchmark was published in 2015, and was sponsored by Volt Active Data. The second was also published in 2015 by End Point, and compared Cassandra against Couchbase, HBase, and MongoDB. This study was commissioned by DataStax, whose main product is powered by Cassandra.
Both of these benchmarks are from 2015. However, there are no reasons to suspect more current versions are less powerful. Both systems have become slightly faster over time, but not significantly so. As such, this comparison is still reasonable.
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Benchmark Methodology Comparison
The first benchmark (Volt Active Data) compared the same system on different hardware, while the second benchmark (Cassandra) compared different systems on the same hardware. Both benchmarks used YCSB workload B, and both looked at costs and operations per second. The full specifications used in this report are as follows.
The Amazon Web Service EC2 Compute Unit (ECU) is referenced a number of times. This is an abstraction of compute power that allows comparisons to be made regardless of the actual hardware involved.
Volt Active Data ran in 6 AWS c4.8xlarge instances. These are large, compute optimized instances. Amazon’s stated use cases for this instance include ad serving and distributed analytics. Each c4.8xlarge has 4,000Mbps bandwidth, 36 CPUs, 132 ECU, 60 GiGB, and EBS-Only Storage at 1.76 $/hr
Cassandra ran in a system comprising 1 to 32 nodes in i2.xlarge instance(s). These are smaller than c4.8xlarge instances. i2.xlarge is recommended for NoSQL databases, in-memory databases, and analytic workloads. It is worth noting that i2.xlarge has been replaced with i3.xlarge. Each i2.xlarge has 500 Mbps bandwidth, 4 CPUs, 14 ECU, 30.5GiB, and 1x800GB SSD at 0.85 $/hr
Comparing 6 c4.8xlarge Volt Active Data nodes with 32 i2.xlarge Cassandra nodes, the summary becomes:
Volt Active Data: 6x c4.8xlarge has 24 Gbps bandwidth, 216 CPUs, 792 ECU, 360 GiGB at 10.56 $/hr
Cassandra: 32x i2.xlarge has 16Gbps bandwidth, 128 CPUs, 448 ECU, 976 GiGB at 27.20 $/hr
While a benchmark using the same exact hardware would be prefered, this configuration is fair for comparing performance relative to hardware. It is worth noting that 6 c4.8xlarge instances are almost 2.5 times cheaper than 32 i2.xlarge instances.
With 6x c4.8xlarge hardware, Volt Active Data achieved 585,137 operations per second.
With 32x i2.xlarge hardware, Cassandra achieved 227,293 operations per second.
|Per Node||Per CPU||Per ECU||Per Mbps||Per GB Memory||Per $ (AWS costs)|
|Volt Active Data||97,523 tps||2709 t/s||739||24.4||1625||55,411|
There are a number of interesting comparisons to draw regardless of hardware differences.
Volt Active Data performs 1.72 times more operations per second per Mbps than Cassandra.
Fast data is all about processing data the instant it arrives. As such, doing the most with bandwidth is key to creating successful fast data applications. Volt Active Data provides more performance with the same amount of bandwidth than Cassandra.
Volt Active Data performs 1.46 times more operations per second per ECU (EC2 Compute Unit) than Cassandra. Profitable fast data applications require getting the most out of the available hardware. By using Cassandra over Volt Active Data on the same hardware, some ECU is essentially wasted.
Volt Active Data performs 6.63 times more operations per second per AWS dollar than Cassandra. When looking at fast data technologies, the cost of running an application can be enormous. The staggering difference in operations per cost further pushes the notion that Volt Active Data can do more with the same.
“We … would have had to do an index lookup on this row-level transac on-id 80,000 mes in order to guarantee idempotency [with Cassandra]. Now contrast this to 336 lookups in case of Volt Active Data. So, for every single index-lookup in Volt Active Data we would have had to do about 238 index lookups in Cassandra or HBase” – Behzad Pirvali, Performance Architect for MaxCDN
Volt Active Data thoroughly beats Cassandra in this comparison, which more than shows that Volt Active Data is comparable to Cassandra in terms of performance, if not better. In addition, Volt Active Data provides more performance per Mbps, per ECU, and per dollar than Cassandra. If you are researching translytical databases, Volt Active Data should be a part of your evaluation.
To learn more, check out the benchmark report, and stay tuned for more Volt Active Data benchmarks.