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Druid vs HBase: What are the differences?
What is Druid? Fast column-oriented distributed data store. Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
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.
Druid belongs to "Big Data Tools" category of the tech stack, while HBase can be primarily classified under "Databases".
"Real Time Aggregations" is the primary reason why developers consider Druid over the competitors, whereas "Performance" was stated as the key factor in picking HBase.
Druid and HBase are both open source tools. Druid with 8.31K GitHub stars and 2.08K forks on GitHub appears to be more popular 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 Druid is used by Airbnb, Instacart, and Dial Once. HBase has a broader approval, being mentioned in 54 company stacks & 18 developers stacks; compared to Druid, which is listed in 24 company stacks and 12 developer stacks.
Pros of Druid
- Real Time Aggregations15
- Batch and Real-Time Ingestion6
- OLAP5
- OLAP + OLTP3
- Combining stream and historical analytics2
- OLTP1
Pros of HBase
- Performance9
- OLTP5
- Fast Point Queries1
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Cons of Druid
- Limited sql support3
- Joins are not supported well2
- Complexity1
Cons of HBase
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What is Druid?
What is HBase?
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