Couchbase vs HBase: What are the differences?
Developers describe Couchbase as "Document-Oriented NoSQL Database". Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands. 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.
Couchbase and HBase can be categorized as "Databases" tools.
"Flexible data model, easy scalability, extremely fast" is the top reason why over 13 developers like Couchbase, while over 7 developers mention "Performance" as the leading cause for choosing 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.
Pinterest, HubSpot, and Yammer are some of the popular companies that use HBase, whereas Couchbase is used by RecordSetter, Musixmatch, and Crowdpark. HBase has a broader approval, being mentioned in 54 company stacks & 18 developers stacks; compared to Couchbase, which is listed in 45 company stacks and 21 developer stacks.
What is Couchbase?
What is HBase?
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We implemented our first large scale EPR application from naologic.com using CouchDB .
Very fast, replication works great, doesn't consume much RAM, queries are blazing fast but we found a problem: the queries were very hard to write, it took a long time to figure out the API, we had to go and write our own @nodejs library to make it work properly.
It lost most of its support. Since then, we migrated to Couchbase and the learning curve was steep but all worth it. Memcached indexing out of the box, full text search works great.
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.
We use Couchbase heavily in our PowerStandings platform to enable real-time analytics of agent data, as well as data storage for parts of our new Playbooks product.
Main data storage. Any writes to Couchbase auto-replicate to Elasticsearch (via XDRC) and from there on propagate into the internal Jezebel pipeline via opes.