HBase vs ToroDB: What are the differences?
Developers describe HBase 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. On the other hand, ToroDB is detailed as "Open source, document-oriented, JSON database that runs on top of PostgreSQL". ToroDB is an open source, document-oriented, JSON database that runs on top of PostgreSQL, providing storage and I/O savings and ACID semantics. ToroDB is MongoDB-compatible, so you can use Mongo clients to connect to it.
HBase and ToroDB belong to "Databases" category of the tech stack.
HBase and ToroDB are both open source tools. It seems that HBase with 2.91K GitHub stars and 2.01K forks on GitHub has more adoption than ToroDB with 10 GitHub stars and 2 GitHub forks.
What is HBase?
What is ToroDB?
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Why do developers choose ToroDB?
What are the cons of using HBase?
What are the cons of using ToroDB?
What companies use ToroDB?
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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.