HBase vs Scylla: What are the differences?
What is 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.
What is Scylla? Next Generation Cassandra. Real-time big data database, with scale-up performance of 1,000,000 IOPS per node, scale-out to 100s of nodes and 99 latency of less than 1 msec.
HBase and Scylla belong to "Databases" category of the tech stack.
HBase and Scylla are both open source tools. It seems that Scylla with 5.18K GitHub stars and 615 forks on GitHub has more adoption than HBase with 2.91K GitHub stars and 2.01K GitHub forks.
Pinterest, HubSpot, and hike are some of the popular companies that use HBase, whereas Scylla is used by Investing.com, Dstillery, and Yieldbot. HBase has a broader approval, being mentioned in 54 company stacks & 18 developers stacks; compared to Scylla, which is listed in 11 company stacks and 5 developer stacks.
What is HBase?
What is Scylla?
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Why do developers choose Scylla?
What are the cons of using HBase?
What are the cons of using Scylla?
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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.
ScyllaDB provides all of the goodies of Apache Cassandra, including HA, multiDC, replication sharding and so forth. The implementation is in C++ and the internal design is better and thus it achieves 10X the throughput, low 99% latency and more