FoundationDB vs HBase: What are the differences?
FoundationDB: Multi-model database with particularly strong fault tolerance, performance, and operational ease. FoundationDB is a NoSQL database with a shared nothing architecture. Designed around a "core" ordered key-value database, additional features and data models are supplied in layers. The key-value database, as well as all layers, supports full, cross-key and cross-server ACID transactions; 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.
FoundationDB and HBase belong to "Databases" category of the tech stack.
"ACID transactions" is the primary reason why developers consider FoundationDB over the competitors, whereas "Performance" was stated as the key factor in picking HBase.
HBase is an open source tool with 2.91K GitHub stars and 2.01K GitHub forks. Here's a link to HBase's open source repository on GitHub.
What is FoundationDB?
What is HBase?
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What are the cons of using FoundationDB?
What are the cons of using HBase?
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What tools integrate with FoundationDB?
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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.