Cassandra vs Druid: What are the differences?
What is Cassandra? A partitioned row store. Rows are organized into tables with a required primary key. Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
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.
Cassandra and Druid are primarily classified as "Databases" and "Big Data" tools respectively.
"Distributed" is the primary reason why developers consider Cassandra over the competitors, whereas "Real Time Aggregations" was stated as the key factor in picking Druid.
Cassandra and Druid are both open source tools. It seems that Druid with 8.32K GitHub stars and 2.08K forks on GitHub has more adoption than Cassandra with 5.27K GitHub stars and 2.35K GitHub forks.
Uber Technologies, Facebook, and Spotify are some of the popular companies that use Cassandra, whereas Druid is used by Airbnb, Instacart, and Streamroot. Cassandra has a broader approval, being mentioned in 342 company stacks & 240 developers stacks; compared to Druid, which is listed in 24 company stacks and 12 developer stacks.
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What is Cassandra?
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