surekhasaharan commented on a change in pull request #6122: New docs intro
URL: https://github.com/apache/incubator-druid/pull/6122#discussion_r208769335
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File path: docs/content/design/index.md
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@@ -2,152 +2,193 @@
layout: doc_page
---
-# Druid Concepts
+# What is Druid?
+
+Druid is a data store designed for high-performance slice-and-dice analytics
+("[OLAP](http://en.wikipedia.org/wiki/Online_analytical_processing)"-style) on
large data sets. Druid is most often
+used as a data store for powering GUI analytical applications, or as a backend
for highly-concurrent APIs that need
+fast aggregations. Common application areas for Druid include:
+
+- Clickstream analytics
+- Network flow analytics
+- Server metrics storage
+- Application performance metrics
+- Digital marketing analytics
+- Business intelligence / OLAP
+
+Druid's key features are:
+
+1. **Columnar storage format.** Druid uses column-oriented storage, meaning it
only needs to load the exact columns
+needed for a particular query. This gives a huge speed boost to queries that
only hit a few columns. In addition, each
+column is stored optimized for its particular data type, which supports fast
scans and aggregations.
+2. **Scalable distributed system.** Druid is typically deployed in clusters of
tens to hundreds of servers, and can
+offer ingest rates of millions of records/sec, retention of trillions of
records, and query latencies of sub-second to a
+few seconds.
+3. **Massively parallel processing.** Druid can process a query in parallel
across the entire cluster.
+4. **Realtime or batch ingestion.** Druid can ingest data either realtime
(ingested data is immediately available for
+querying) or in batches.
+5. **Self-healing, self-balancing, easy to operate.** As an operator, to scale
the cluster up or down, simply add or
Review comment:
I think more correct term might be be `to scale the cluster out or in,`
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