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Druid

Druid is a high-performance, real-time analytics database designed for fast slice-and-dice queries on large datasets. It excels at ingesting event streams and providing low-latency query responses, making it ideal for interactive data applications and real-time dashboards.

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About Druid

Druid was created in 2011 by the engineering team at Metamarkets to address the need for a high-performance, real-time analytics database. The team developed Druid to handle large-scale event streams and enable low-latency querying, aiming to enhance their data analysis capabilities for interactive applications.

Druid's strengths include real-time data ingestion, low-latency query performance, and scalability for large datasets. Its weaknesses involve complex setup and maintenance, limited support for transactional workloads, and potential challenges with schema evolution. Competitors include Apache Pinot, ClickHouse, and Google BigQuery.

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How to hire a Druid expert

A Druid expert must have strong skills in data modeling, proficiency in query languages like SQL, and experience with real-time data ingestion frameworks such as Apache Kafka. They should also be adept at managing and tuning distributed systems, possess knowledge of cloud infrastructure, and understand performance optimization techniques specific to Druid.

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