<!DOCTYPE html><html lang="en"><head><meta charSet="utf-8"/><meta http-equiv="X-UA-Compatible" content="IE=edge"/><title>Apache Druid vs Kudu · Apache Druid</title><meta name="viewport" content="width=device-width"/><link rel="canonical" href="https://druid.apache.org/docs/0.20.1/comparisons/druid-vs-kudu.html"/><meta name="generator" content="Docusaurus"/><meta name="description" content="&lt;!--"/><meta name="docsearch:language" content="en"/><meta name="docsearch:version" content="0.20.1" /><meta property="og:title" content="Apache Druid vs Kudu · Apache Druid"/><meta property="og:type" content="website"/><meta property="og:url" content="https://druid.apache.org/index.html"/><meta property="og:description" content="&lt;!--"/><meta property="og:image" content="https://druid.apache.org/img/druid_nav.png"/><meta name="twitter:card" content="summary"/><meta name="twitter:image" content="https://druid.apache.org/img/druid_nav.png"/><link rel="shortcut icon" href="/img/favicon.png"/><link rel="stylesheet" href="https://cdn.jsdelivr.net/docsearch.js/1/docsearch.min.css"/><link rel="stylesheet" href="//cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/styles/default.min.css"/><script async="" src="https://www.googletagmanager.com/gtag/js?id=UA-131010415-1"></script><script>
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UIs</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/operations/deep-storage-migration.html">Deep storage migration</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/operations/export-metadata.html">Export Metadata Tool</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/operations/metadata-migration.html">Metadata Migration</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/operations/segment-optimization.html">Segment Size Optimization</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/operations/use_sbt_to_build_fat_jar.html">Content for build.sbt</a></li></ul></div></ul></div><div class="navGroup"><h3 class="navGroupCategoryTitle collapsible">Development<span class="arrow"><svg width="24" height="24" viewBox="0 0 24 24"><path fill="#565656" d="M7.41 15.41L12 10.83l4.59 4.58L18 14l-6-6-6 6z"></path><path d="M0 0h24v24H0z" fill="none"></path></svg></span></h3><ul class="hide"><li 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Redshift</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/comparisons/druid-vs-spark.html">Apache Druid vs Spark</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/comparisons/druid-vs-sql-on-hadoop.html">Apache Druid vs SQL-on-Hadoop</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/design/auth.html">Authentication and Authorization</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/design/broker.html">Broker</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/design/coordinator.html">Coordinator Process</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/design/historical.html">Historical Process</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/design/indexer.html">Indexer Process</a></li><li class="navListItem"><a class="navItem" href="/docs/0.20.1/design/indexing-service.html">Indexing Service</a></li><li class="navListItem"><a class="navItem" 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<p>Kudu's storage format enables single row updates, whereas updates to existing Druid segments requires recreating the segment, so theoretically
the process for updating old values should be higher latency in Druid. However, the requirements in Kudu for maintaining extra head space to store
updates as well as organizing data by id instead of time has the potential to introduce some extra latency and accessing
of data that is not need to answer a query at query time.</p>
<p>Druid summarizes/rollups up data at ingestion time, which in practice reduces the raw data that needs to be
stored significantly (up to 40 times on average), and increases performance of scanning raw data significantly.
Druid segments also contain bitmap indexes for fast filtering, which Kudu does not currently support.
Druid's segment architecture is heavily geared towards fast aggregates and filters, and for OLAP workflows. Appends are very
fast in Druid, whereas updates of older data is higher latency. This is by design as the data Druid is good for is typically event data,
and does not need to be updated too frequently. Kudu supports arbitrary primary keys with uniqueness constraints, and
efficient lookup by ranges of those keys. Kudu chooses not to include the execution engine, but supports sufficient
operations so as to allow node-local processing from the execution engines. This means that Kudu can support multiple frameworks on the same data (e.g., MR, Spark, and SQL).
Druid includes its own query layer that allows it to push down aggregations and computations directly to data processes for faster query processing.</p>
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