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Druid vs Pilosa: What are the differences?
Developers describe Druid as "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. On the other hand, Pilosa is detailed as "Open source, distributed bitmap index in Go". Pilosa is an open source, distributed bitmap index that dramatically accelerates queries across multiple, massive data sets.
Druid and Pilosa can be primarily classified as "Big Data" tools.
Druid and Pilosa are both open source tools. Druid with 8.31K GitHub stars and 2.08K forks on GitHub appears to be more popular than Pilosa with 1.83K GitHub stars and 149 GitHub forks.
Pros of Druid
- Real Time Aggregations15
- Batch and Real-Time Ingestion6
- OLAP5
- OLAP + OLTP3
- Combining stream and historical analytics2
- OLTP1
Pros of Pilosa
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Cons of Druid
- Limited sql support3
- Joins are not supported well2
- Complexity1
Cons of Pilosa
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What is Druid?
What is Pilosa?
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What companies use Pilosa?
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