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Merge pull request #47 from implydata/autobuild
Autobuild
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vogievetsky committed Nov 8, 2019
2 parents 27d5345 + 9a4e9e1 commit 4db6362fe547b227ea83de835c7c407487a68b8d
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@@ -153,7 +153,7 @@ <h5>Dead easy integration with your existing data pipeline</h5>
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<h5>100x faster than traditional solutions</h5>
<h5>Up to 100x faster than traditional solutions</h5>
<p>
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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@@ -169,7 +169,7 @@ <h5>Unlock new workflows</h5>
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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 processes.
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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@@ -296,6 +296,15 @@ <h3>
Featured Content
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<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>
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<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>
@@ -332,15 +341,6 @@ <h3>
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<a href="https://www.fullcontact.com/blog/enrich-api-brings-higher-match-rates-with-multi-field-enrichment-capabilities/">
<span class="title">Enrich API Brings Higher Match Rates with Multi-Field Enrichment Capabilities</span><br>
<span class="text-muted">Ken Michie - </span>
<span class="text-muted">FullContact</span><br>
<span class="text-muted">Jun 27 2019</span>
</a>
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@@ -248,12 +248,12 @@ <h2 id="querying">Querying</h2>
<h2 id="architecture">Architecture</h2>

<p>Druid has a microservice-based architecture can be thought of as a disassembled database.
Each core process in Druid (ingestion, querying, and coordination) can be separately or jointly deployed on commodity hardware.</p>
Each core service in Druid (ingestion, querying, and coordination) can be separately or jointly deployed on commodity hardware.</p>

<p>Druid explicitly names every main process to allow the operator to fine tune each process based on the use case and workload.
For example, an operator can dedicate more resources to Druid’s ingestion process while giving less resources to Druid’s query process if the workload requires it.</p>
<p>Druid explicitly names every main service to allow the operator to fine tune each service based on the use case and workload.
For example, an operator can dedicate more resources to Druid’s ingestion service while giving less resources to Druid’s query service if the workload requires it.</p>

<p>Druid processes can independently fail without impacting the operations of other processes.</p>
<p>Druid services can independently fail without impacting the operations of other services.</p>

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@@ -276,11 +276,11 @@ <h5>Data replication</h5>
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<h5>Independent processes</h5>
<h5>Independent services</h5>
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Druid explicitly names all of its main processes and each process can be fine tuned based on use case.
Processes can independently fail without impacting other processes.
For example, if the ingestion process fails, no new data is loaded in the system, but existing data remains queryable.
Druid explicitly names all of its main services and each service can be fine tuned based on use case.
Services can independently fail without impacting other services.
For example, if the ingestion services fails, no new data is loaded in the system, but existing data remains queryable.
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