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Amazon Redshift Spectrum vs Druid: What are the differences?
What is Amazon Redshift Spectrum? Exabyte-Scale In-Place Queries of S3 Data. With Redshift Spectrum, you can extend the analytic power of Amazon Redshift beyond data stored on local disks in your data warehouse to query vast amounts of unstructured data in your Amazon S3 “data lake” -- without having to load or transform any data.
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.
Amazon Redshift Spectrum and Druid can be categorized as "Big Data" tools.
Druid is an open source tool with 8.31K GitHub stars and 2.08K GitHub forks. Here's a link to Druid's open source repository on GitHub.
According to the StackShare community, Druid has a broader approval, being mentioned in 24 company stacks & 12 developers stacks; compared to Amazon Redshift Spectrum, which is listed in 5 company stacks and 4 developer stacks.
Pros of Amazon Redshift Spectrum
- Good Performance1
- Great Documentation1
- Economical1
Pros of Druid
- Real Time Aggregations15
- Batch and Real-Time Ingestion6
- OLAP5
- OLAP + OLTP3
- Combining stream and historical analytics2
- OLTP1
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Cons of Amazon Redshift Spectrum
Cons of Druid
- Limited sql support3
- Joins are not supported well2
- Complexity1
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What is Amazon Redshift Spectrum?
What is Druid?
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What companies use Druid?
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