gianm commented on a change in pull request #66: new stuff
URL:
https://github.com/apache/incubator-druid-website-src/pull/66#discussion_r337147351
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File path: index.html
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@@ -29,30 +29,30 @@ <h2>
<div class="features">
<div class="feature">
<span class="fa fa-chart-line fa"></span>
- <h5>Analyze event streams</h5>
+ <h5>Power applications where low latency really matters</h5>
<p>
- Druid provides fast analytical queries, at high concurrency, on
event-driven data. Druid can instantaneously ingest streaming data and provide
sub-second queries to power interactive UIs.
+ Druid is a real-time analytics database that excels at providing
immediate data visibility and understanding. Easily load streaming or batch
data, and answer ad-hoc analytic queries on billions of rows in under a second.
</p>
</div>
<div class="feature">
- <span class="fa fa-lightbulb fa"></span>
- <h5>Utilize reimagined architecture</h5>
+ <span class="fa fa-forward fa"></span>
+ <h5>Build event-driven data stacks</h5>
<p>
- Druid is a new type of database that combines ideas from <a
href='https://en.wikipedia.org/wiki/Online_analytical_processing'>OLAP/analytic
databases</a>, <a
href='https://en.wikipedia.org/wiki/Time_series_database'>timeseries
databases</a>, and <a
href='https://en.wikipedia.org/wiki/Full-text_search'>search systems</a> to
enable new use cases in streaming architectures.
+ Druid is a query layer that that natively integrates with message
buses (<a href='http://kafka.apache.org/'>Kafka</a>, <a
href='https://aws.amazon.com/kinesis/'>AWS Kinesis</a>, etc) and data lakes (<a
href='https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsUserGuide.html'>HDFS</a>,
<a href='https://aws.amazon.com/s3/'>AWS S3</a>, etc). Build end-to-end data
stacks ideal for streaming data.
Review comment:
I usually describe Druid as _not_ a query layer, in the sense that it stores
data inside itself, and doesn't query it live from somewhere else.
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