Event Store vs HBase: What are the differences?
Developers describe Event Store as "The open-source, functional database with Complex Event Processing *". It stores your data as a series of immutable events over time, making it easy to build event-sourced applications. It can run as a cluster of nodes containing the same data, which remains available for writes provided at least half the nodes are alive and connected. On the other hand, *HBase** is detailed as "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.
Event Store and HBase belong to "Databases" category of the tech stack.
HBase is an open source tool with 3K GitHub stars and 2.05K GitHub forks. Here's a link to HBase's open source repository on GitHub.
According to the StackShare community, HBase has a broader approval, being mentioned in 69 company stacks & 109 developers stacks; compared to Event Store, which is listed in 9 company stacks and 11 developer stacks.
What is Event Store?
What is HBase?
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Why do developers choose Event Store?
What are the cons of using Event Store?
What are the cons of using HBase?
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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.