Azure SQL Database vs HBase: What are the differences?
Developers describe Azure SQL Database as "Managed, intelligent SQL in the cloud". It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software. 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.
Azure SQL Database and HBase can be primarily classified as "Databases" tools.
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.
Pinterest, HubSpot, and hike are some of the popular companies that use HBase, whereas Azure SQL Database is used by Property With Potential, Kriasoft, and vLearning Solutions. HBase has a broader approval, being mentioned in 69 company stacks & 109 developers stacks; compared to Azure SQL Database, which is listed in 21 company stacks and 20 developer stacks.
What is Azure SQL Database?
What is HBase?
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Why do developers choose Azure SQL Database?
What are the cons of using Azure SQL Database?
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.