Druid vs Apache Flink: What are the differences?
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; Apache Flink: Fast and reliable large-scale data processing engine. Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
Druid and Apache Flink belong to "Big Data Tools" category of the tech stack.
"Real Time Aggregations" is the primary reason why developers consider Druid over the competitors, whereas "Unified batch and stream processing" was stated as the key factor in picking Apache Flink.
Druid and Apache Flink are both open source tools. Apache Flink with 9.11K GitHub stars and 4.86K forks on GitHub appears to be more popular than Druid with 8.22K GitHub stars and 2.05K GitHub forks.
Zalando, sovrn Holdings, and BetterCloud are some of the popular companies that use Apache Flink, whereas Druid is used by Instacart, Airbnb, and Dial Once. Apache Flink has a broader approval, being mentioned in 20 company stacks & 21 developers stacks; compared to Druid, which is listed in 24 company stacks and 12 developer stacks.
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