Have you ever been in a situation where you don’t know which one you need, whether it is HBase or Cassandra? You’re not alone, after all, they both belong to the Apache brand and are both NoSQL wide-column stores, so it’s not surprising. Although, the dilemma deepens on a closer look when the differences start popping up and then one has to be left for the other.
1. Query Language
One of the main differences is the presence of a query language. HBase is devoid of a query language and will require other techs for it. Whereas, Cassandra has its own query language, Cassandra Query Language (CQL).
Secondly, they differ largely in terms of their architecture. HBase operates on a master-based structure. However, Cassandra functions on a framework without a master. HBase has a downtime regarding communication with the server, especially when the master is down, while the Cassandra cluster requires no working time, as it is readily accessible and available.
3. Inconsistent Data
Thirdly, as a result of the above issue of downtime, the unbroken availability of Cassandra comes with a price. There is a necessary data duplication for persistent accessibility, which can inconsistency in the data being copied. However, HBase evades this conflict with its incorporation of the slave-server the master-based cluster, allowing data to be deposited in one unified center removing the issue of inconsistency.
4. Write Paths
Furthermore, they both have similar on-server write paths, but HBase is slightly at a disadvantage when compared to Cassandra. HBase’s write performance clocks about 300,000 operations per second, while the performance of Cassandra at writes is way above that of HBase with well over 320,000 operations per second in a 32-node cluster.
5. Read per Seconds
Additionally, when dealing with reads, multiple factors play a role in deciding which is better. When scans, random access to data, and consistency are put into consideration, then HBase can actually compete with Cassandra despite the remarkable numbers it puts up in a 32-node cluster reads per second.
Both of them are secure, but they differ slightly in execution. This is already evident from the difference in architecture. HBase and Cassandra offer accessibility to databases with reasonable control leverage left for administrators. HBase gives admins the power to decide the visibility level of each data set and in turn notify users accordingly. This is different from Cassandra which allows admins to define the role of the users and put the visibility settings for those roles. Also, HBase gives access all the way to individual cells, while Cassandra allows access to the rows.
HBase and Cassandra can be applied reasonably in projects concerning time-series data. IoT is rapidly evolving and both HBase and Cassandra can process the sensor readings in the Internet of Things framework. They can also be used to analyze stock exchange datasets.
On balance, however, both are of the same family but professionals will find them more fitting for particular projects. What primarily separates HBase and Cassandra respectively regarding their application to tasks is that one is better suited to developing machine learning standards, while the other is perfect for online mobile apps and real-time analytics. To identify which of these two are suitable for your project, contact us at Codeupset.