EdgeDB vs HBase: What are the differences?
Developers describe EdgeDB as "The Next Generation Object-Relational Database". An object-relational database that stores and describes the data as strongly typed objects and relationships between them. 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.
EdgeDB and HBase can be categorized as "Databases" tools.
EdgeDB and HBase are both open source tools. EdgeDB with 3.01K GitHub stars and 64 forks on GitHub appears to be more popular than HBase with 2.91K GitHub stars and 2.01K GitHub forks.
What is EdgeDB?
What is HBase?
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Why do developers choose EdgeDB?
What are the cons of using EdgeDB?
What are the cons of using HBase?
What companies use EdgeDB?
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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.