mirror of https://github.com/apache/druid.git
40 lines
1.6 KiB
Markdown
40 lines
1.6 KiB
Markdown
---
|
|
layout: doc_page
|
|
title: "Integrating Druid With Other Technologies"
|
|
---
|
|
|
|
<!--
|
|
~ Licensed to the Apache Software Foundation (ASF) under one
|
|
~ or more contributor license agreements. See the NOTICE file
|
|
~ distributed with this work for additional information
|
|
~ regarding copyright ownership. The ASF licenses this file
|
|
~ to you under the Apache License, Version 2.0 (the
|
|
~ "License"); you may not use this file except in compliance
|
|
~ with the License. You may obtain a copy of the License at
|
|
~
|
|
~ http://www.apache.org/licenses/LICENSE-2.0
|
|
~
|
|
~ Unless required by applicable law or agreed to in writing,
|
|
~ software distributed under the License is distributed on an
|
|
~ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
|
|
~ KIND, either express or implied. See the License for the
|
|
~ specific language governing permissions and limitations
|
|
~ under the License.
|
|
-->
|
|
|
|
# Integrating Druid With Other Technologies
|
|
|
|
This page discusses how we can integrate Druid with other technologies.
|
|
|
|
## Integrating with Open Source Streaming Technologies
|
|
|
|
Event streams can be stored in a distributed message bus such as Kafka and further processed via a distributed stream
|
|
processor system such as Storm, Samza, or Spark Streaming. Data processed by the stream processor can feed into Druid using
|
|
the [Tranquility](https://github.com/druid-io/tranquility) library.
|
|
|
|
<img src="../../img/druid-production.png" width="800"/>
|
|
|
|
## Integrating with SQL-on-Hadoop Technologies
|
|
|
|
Druid should theoretically integrate well with SQL-on-Hadoop technologies such as Apache Drill, Spark SQL, Presto, Impala, and Hive.
|