CrateIO vs HBase: What are the differences?
CrateIO: The Distributed Database for Docker. Crate is a distributed data store. Simply install Crate directly on your application servers and make the big centralized database a thing of the past. Crate takes care of synchronization, sharding, scaling, and replication even for mammoth data sets; 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.
CrateIO and HBase can be primarily classified as "Databases" tools.
"Simplicity" is the primary reason why developers consider CrateIO over the competitors, whereas "Performance" was stated as the key factor in picking HBase.
CrateIO and HBase are both open source tools. HBase with 2.91K GitHub stars and 2.01K forks on GitHub appears to be more popular than CrateIO with 2.49K GitHub stars and 333 GitHub forks.
What is CrateIO?
What is HBase?
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What are the cons of using CrateIO?
What are the cons of using HBase?
What companies use CrateIO?
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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.