Druid vs MongoDB: 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; MongoDB: The database for giant ideas. MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Druid and MongoDB are primarily classified as "Big Data" and "Databases" tools respectively.
"Real Time Aggregations" is the top reason why over 3 developers like Druid, while over 788 developers mention "Document-oriented storage" as the leading cause for choosing MongoDB.
Druid and MongoDB are both open source tools. MongoDB with 16.3K GitHub stars and 4.1K forks on GitHub appears to be more popular than Druid with 8.32K GitHub stars and 2.08K GitHub forks.
According to the StackShare community, MongoDB has a broader approval, being mentioned in 2189 company stacks & 2225 developers stacks; compared to Druid, which is listed in 24 company stacks and 12 developer stacks.
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