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new abdf9ea ORC-1071: Update adopters page (#985)
abdf9ea is described below
commit abdf9ea27a80abeb6c4f300ce5a4f0a03abe4615
Author: Dongjoon Hyun <[email protected]>
AuthorDate: Thu Dec 30 18:34:58 2021 -0800
ORC-1071: Update adopters page (#985)
---
docs/adopters.html | 48 +++++++++++++++++++++++++++++++++++++++++-------
1 file changed, 41 insertions(+), 7 deletions(-)
diff --git a/docs/adopters.html b/docs/adopters.html
index 0d09752..b812e4a 100644
--- a/docs/adopters.html
+++ b/docs/adopters.html
@@ -831,6 +831,33 @@ but with the ORC 1.1.0 release it is now easier than ever
without pulling in
Hive’s exec jar and all of its dependencies. OrcStruct now also implements
WritableComparable and can be serialized through the MapReduce shuffle.</p>
+<h3 id="apache-spark"><a href="https://spark.apache.org/";>Apache Spark</a></h3>
+
+<p>Apache Spark has <a
href="https://databricks.com/blog/2015/07/16/joint-blog-post-bringing-orc-support-into-apache-spark.html";>added
+support</a>
+for reading and writing ORC files with support for column project and
+predicate push down.</p>
+
+<h3 id="apache-arrow"><a href="https://arrow.apache.org/";>Apache Arrow</a></h3>
+
+<p>Apache Arrow supports reading and writing <a
href="https://arrow.apache.org/docs/index.html?highlight=orc#apache-arrow";>ORC
file format</a>.</p>
+
+<h3 id="apache-flink"><a href="https://flink.apache.org/";>Apache Flink</a></h3>
+
+<p>Apache Flink supports
+<a
href="https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/connectors/table/formats/orc/";>ORC
format in Table API</a>
+for reading and writing ORC files.</p>
+
+<h3 id="apache-iceberg"><a href="https://iceberg.apache.org/";>Apache
Iceberg</a></h3>
+
+<p>Apache Iceberg supports <a href="https://iceberg.apache.org/#spec/#orc";>ORC
spec</a> to use ORC tables.</p>
+
+<h3 id="apache-druid"><a href="https://druid.apache.org/";>Apache Druid</a></h3>
+
+<p>Apache Druid supports
+<a
href="https://druid.apache.org/docs/0.22.1/development/extensions-core/orc.html#orc-extension";>ORC
extension</a>
+to ingest and understand the Apache ORC data format.</p>
+
<h3 id="apache-hive"><a href="https://hive.apache.org/";>Apache Hive</a></h3>
<p>Apache Hive was the original use case and home for ORC. ORC’s strong
@@ -839,6 +866,12 @@ down, and vectorization support make Hive <a
href="https://hortonworks.com/blog/
better</a>
than any other format for your data.</p>
+<h3 id="apache-gobblin"><a href="https://gobblin.apache.org/";>Apache
Gobblin</a></h3>
+
+<p>Apache Gobblin supports
+<a
href="https://gobblin.apache.org/docs/case-studies/Writing-ORC-Data/";>writing
data to ORC files</a>
+by leveraging Apache Hive’s SerDe library.</p>
+
<h3 id="apache-nifi"><a href="https://nifi.apache.org/";>Apache Nifi</a></h3>
<p>Apache Nifi is <a
href="https://issues.apache.org/jira/browse/NIFI-1663";>adding
@@ -850,13 +883,6 @@ ORC files.</p>
<p>Apache Pig added support for reading and writing ORC files in <a
href="https://hortonworks.com/blog/announcing-apache-pig-0-14-0/";>Pig
14.0</a>.</p>
-<h3 id="apache-spark"><a href="https://spark.apache.org/";>Apache Spark</a></h3>
-
-<p>Apache Spark has <a
href="https://databricks.com/blog/2015/07/16/joint-blog-post-bringing-orc-support-into-apache-spark.html";>added
-support</a>
-for reading and writing ORC files with support for column project and
-predicate push down.</p>
-
<h3 id="eel"><a href="https://github.com/51zero/eel-sdk";>EEL</a></h3>
<p>EEL is a Scala BigData API that supports reading and writing data for
@@ -875,6 +901,14 @@ or directly into Hive tables backed by an ORC file
format.</p>
<p>With more than 300 PB of data, Facebook was an <a
href="https://code.facebook.com/posts/229861827208629/scaling-the-facebook-data-warehouse-to-300-pb/";>early
adopter of
ORC</a> and quickly put it into production.</p>
+<h3 id="linkedin"><a href="https://linkedin.com";>LinkedIn</a></h3>
+
+<p>LinkedIn uses
+<a
href="https://engineering.linkedin.com/blog/2021/fastingest-low-latency-gobblin";>the
ORC file format</a>
+with Apache Iceberg metadata catalog and Apache Gobblin to provide our data
customers with high-query performance.</p>
+
+<p>https://engineering.linkedin.com/blog/2021/fastingest-low-latency-gobblin</p>
+
<h3 id="trino-formerly-presto-sql"><a href="https://trino.io/";>Trino (formerly
Presto SQL)</a></h3>
<p>The Trino team has done a lot of work <a
href="https://code.facebook.com/posts/370832626374903/even-faster-data-at-the-speed-of-presto-orc/";>integrating
