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| <p class="lead">Apache Druid is a high performance real-time analytics database.</p> |
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| Overview |
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| <h5>A modern cloud-native, stream-native, analytics database</h5> |
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| 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 <a href='/use-cases'>use cases</a>. |
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| <h5>Easy integration with your existing data pipelines</h5> |
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| Druid can natively stream data from message buses such as <a href='http://kafka.apache.org/'>Kafka</a>, <a href='https://aws.amazon.com/kinesis/'>Amazon Kinesis</a>, and more, and batch load files from data lakes such as <a href='https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsUserGuide.html'>HDFS</a>, <a href='https://aws.amazon.com/s3/'>Amazon S3</a>, and more. |
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| <h5>Up to 100x faster than traditional solutions</h5> |
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| Druid has been <a href='https://imply.io/post/performance-benchmark-druid-presto-hive'>benchmarked</a> to greatly outpeform legacy solutions for data ingestion and data querying. Druid's novel architecture combines the best of <a href='https://en.wikipedia.org/wiki/Data_warehouse'>data warehouses</a>, <a href='https://en.wikipedia.org/wiki/Time_series_database'>timeseries databases</a>, and <a href='https://en.wikipedia.org/wiki/Search_engine_(computing)'>search systems</a>. |
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| <h5>Unlock new workflows</h5> |
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| Druid <a href='/use-cases'>unlocks new types of queries and workflows</a> 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. |
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| <h5>Deploy in AWS/GCP/Azure, hybrid clouds, Kubernetes, and bare metal</h5> |
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| 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. |
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| Learn more |
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| Druid is proven in production at the <a href='/druid-powered'>world’s leading companies</a> at massive scale. |
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| Learn about some of the <a href='faq'>most common questions about Druid</a>. |
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| <a href="/docs/latest/tutorials/quickstart">Get started with Druid</a> in minutes. Load your own data and query it. |
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| Get help from a <a href='/community'>wide network of community members</a> about using Druid. |
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| Jan |
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| 25 |
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| <p> |
| <a href="https://datadaytexas.com/2020/sessions#merlino"> |
| <span class ="title">Data Day Texas</span><br> |
| <span class="text-muted">AT&T Executive Education & Conference Center - 1900 University Avenue - Austin, TX 78705</span> |
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| <a href="https://www.meetup.com/Athens-Big-Data/events/266900242/"> |
| <span class ="title">Athens Big Data Meetup</span><br> |
| <span class="text-muted">Alba Graduate Business School, 6-8 Xenias Str, Athens</span> |
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| <a href="https://www.meetup.com/Big-things-are-happening-here/events/267578817/"> |
| <span class ="title">Implementing, optimizing and using Apache Druid at scale</span><br> |
| <span class="text-muted">Nielsen R&D Israel, Derech Menachem Begin 121 Azrieli Sarona Azrieli Sarona, 18th floor, Tel Aviv-Yafo</span> |
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| <span class ="title">Druid Summit</span><br> |
| <span class="text-muted">San Francisco Airport Marriott Waterfront, 1800 Old Bayshore Highway, Burlingame, CA</span> |
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| Featured Content |
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| <p> |
| <a href="https://imply.io/post/reflecting-on-druid"> |
| <span class="title">Druid: Reflections at a Milestone</span><br> |
| <span class="text-muted">Gian Merlino - </span> |
| <span class="text-muted">Imply</span><br> |
| <span class="text-muted">Dec 10 2019</span> |
| </a> |
| </p> |
| |
| <p> |
| <a href="https://imply.io/post/nielsen-marketing-audience-analysis"> |
| <span class="title">How Nielsen Marketing Cloud Uses Druid for Audience and Marketing Performance Analysis</span><br> |
| <span class="text-muted">Itai Yaffe - </span> |
| <span class="text-muted">Nielsen</span><br> |
| <span class="text-muted">Nov 21 2019</span> |
| </a> |
| </p> |
| |
| <p> |
| <a href="https://imply.io/post/druid-console-query-view"> |
| <span class="title">Druid query view: An elegant SQL interface for a more civilized age</span><br> |
| <span class="text-muted">Margaret Brewster - </span> |
| <span class="text-muted">Imply</span><br> |
| <span class="text-muted">Oct 16 2019</span> |
| </a> |
| </p> |
| |
| <p> |
| <a href="https://medium.com/nmc-techblog/data-retention-and-deletion-in-apache-druid-74ffd12398a8"> |
| <span class="title">Data Retention and Deletion in Apache Druid</span><br> |
| <span class="text-muted">Dana Assa and Itai Yaffe - </span> |
| <span class="text-muted">Nielsen</span><br> |
| <span class="text-muted">Sep 15 2019</span> |
| </a> |
| </p> |
| |
| <p> |
| <a href="https://medium.com/outbrain-engineering/understanding-spark-streaming-with-kafka-and-druid-25b69e28dcb7"> |
| <span class="title">Understanding Spark Streaming with Kafka and Druid</span><br> |
| <span class="text-muted">Daria Litvinov - </span> |
| <span class="text-muted">Outbrain</span><br> |
| <span class="text-muted">Aug 11 2019</span> |
| </a> |
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| Latest releases |
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| <a href="https://github.com/apache/incubator-druid/releases/tag/druid-0.17.0"> |
| <span class="title">Apache Druid 0.17.0 Released</span><br> |
| <span class="text-muted">Jan 26 2020</span> |
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| <a href="https://github.com/apache/incubator-druid/releases/tag/druid-0.16.1-incubating"> |
| <span class="title">Apache Druid 0.16.1 Released</span><br> |
| <span class="text-muted">Dec 10 2019</span> |
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