Druid vs Elasticsearch: 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 Elasticsearch? Open Source, Distributed, RESTful Search Engine. Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
Druid can be classified as a tool in the "Big Data Tools" category, while Elasticsearch is grouped under "Search as a Service".
"Real Time Aggregations" is the primary reason why developers consider Druid over the competitors, whereas "Powerful api" was stated as the key factor in picking Elasticsearch.
Druid and Elasticsearch are both open source tools. It seems that Elasticsearch with 42.4K GitHub stars and 14.2K forks on GitHub has more adoption than Druid with 8.32K GitHub stars and 2.08K GitHub forks.
According to the StackShare community, Elasticsearch has a broader approval, being mentioned in 2003 company stacks & 979 developers stacks; compared to Druid, which is listed in 24 company stacks and 12 developer stacks.
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