HBase vs Riak: What are the differences?
HBase: The Hadoop database, a distributed, scalable, big data store. Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop; Riak: A distributed, decentralized data storage system. Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data.
HBase and Riak belong to "Databases" category of the tech stack.
"Performance" is the primary reason why developers consider HBase over the competitors, whereas "High Performance " was stated as the key factor in picking Riak.
HBase and Riak are both open source tools. Riak with 3.24K GitHub stars and 530 forks on GitHub appears to be more popular than HBase with 2.91K GitHub stars and 2.01K GitHub forks.
According to the StackShare community, HBase has a broader approval, being mentioned in 54 company stacks & 18 developers stacks; compared to Riak, which is listed in 15 company stacks and 10 developer stacks.
What is HBase?
What is Riak?
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What are the cons of using HBase?
What are the cons of using Riak?
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The final output is inserted into HBase to serve the experiment dashboard. We also load the output data to Redshift for ad-hoc analysis. For real-time experiment data processing, we use Storm to tail Kafka and process data in real-time and insert metrics into MySQL, so we could identify group allocation problems and send out real-time alerts and metrics.