Druid is designed for workflows where fast queries and ingest really matter. Druid excels at instant data visibility, ad-hoc queries, operational analytics, and handling high concurrency. Consider Druid as an open source alternative to data warehouses for a variety of use cases.
Druid can natively stream data from message buses such as Kafka, Amazon Kinesis, and more, and batch load files from data lakes such as HDFS, Amazon S3, and more.
Druid has been benchmarked to greatly outpeform legacy solutions for data ingestion and data querying. Druid's novel architecture combines the best of data warehouses, timeseries databases, and search systems.
Druid unlocks new types of queries and workflows for clickstream, APM, supply chain, network telemetry, digital marketing, and many other forms of event-driven data. Druid is purpose built for rapid, ad-hoc queries on both real-time and historical data.
Druid can be deployed in any *NIX environment on commodity hardware, both in the cloud and on premise. Deploying Druid is easy: scaling up and down is as simple as adding and removing Druid services.
Druid is proven in production at the world’s leading companies at massive scale.
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Druid Summit
San Francisco Airport Marriott Waterfront, 1800 Old Bayshore Highway, Burlingame, CA
Apache Druid Vision and Roadmap
Gian Merlino -
Imply
Apr 15 2020
Apache Druid for Anti-Money Laundering (AML) at DBS Bank
Arpit Dubey -
DBS
Apr 15 2020
How Apache Druid Powers Real-Time Analytics at BT
Pankaj Tiwari -
BT
Apr 15 2020
Analytics over Terabytes of Data at Twitter using Apache Druid
Swapnesh Gandhi -
MoPub
Apr 15 2020