HBase vs PipelineDB: What are the differences?
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; PipelineDB: The Streaming SQL Database. PipelineDB is an open-source relational database that runs SQL queries continuously on streams, incrementally storing results in tables.
HBase and PipelineDB can be primarily classified as "Databases" tools.
HBase is an open source tool with 3.35K GitHub stars and 2.28K GitHub forks. Here's a link to HBase's open source repository on GitHub.
What is HBase?
What is PipelineDB?
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Why do developers choose PipelineDB?
What are the cons of using HBase?
What are the cons of using PipelineDB?
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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.