ORC-1071: Update adopters page (#985)

### What changes were proposed in this pull request?
This PR aims to update the [adopters page](https://orc.apache.org/docs/adopters.html). 

### Why are the changes needed?
To make it up-to-date. 

### How was this patch tested?
Manually review.

site/_docs/adopters.md

@@ -14,6 +14,33 @@ 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.
 
+### [Apache Spark](https://spark.apache.org/)
+
+Apache Spark has [added
+support](https://databricks.com/blog/2015/07/16/joint-blog-post-bringing-orc-support-into-apache-spark.html)
+for reading and writing ORC files with support for column project and
+predicate push down.
+
+### [Apache Arrow](https://arrow.apache.org/)
+
+Apache Arrow supports reading and writing [ORC file format](https://arrow.apache.org/docs/index.html?highlight=orc#apache-arrow).
+
+### [Apache Flink](https://flink.apache.org/)
+
+Apache Flink supports
+[ORC format in Table API](https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/connectors/table/formats/orc/)
+for reading and writing ORC files.
+
+### [Apache Iceberg](https://iceberg.apache.org/)
+
+Apache Iceberg supports [ORC spec](https://iceberg.apache.org/#spec/#orc) to use ORC tables.
+
+### [Apache Druid](https://druid.apache.org/)
+
+Apache Druid supports
+[ORC extension](https://druid.apache.org/docs/0.22.1/development/extensions-core/orc.html#orc-extension)
+to ingest and understand the Apache ORC data format.
+
 ### [Apache Hive](https://hive.apache.org/)
 
 Apache Hive was the original use case and home for ORC.  ORC's strong
@@ -22,6 +49,12 @@ down, and vectorization support make Hive [perform
 better](https://hortonworks.com/blog/orcfile-in-hdp-2-better-compression-better-performance/)
 than any other format for your data.
 
+### [Apache Gobblin](https://gobblin.apache.org/)
+
+Apache Gobblin supports
+[writing data to ORC files](https://gobblin.apache.org/docs/case-studies/Writing-ORC-Data/)
+by leveraging Apache Hive's SerDe library.
+
 ### [Apache Nifi](https://nifi.apache.org/)
 
 Apache Nifi is [adding
@@ -33,13 +66,6 @@ ORC files.
 Apache Pig added support for reading and writing ORC files in [Pig
 14.0](https://hortonworks.com/blog/announcing-apache-pig-0-14-0/).
 
-### [Apache Spark](https://spark.apache.org/)
-
-Apache Spark has [added
-support](https://databricks.com/blog/2015/07/16/joint-blog-post-bringing-orc-support-into-apache-spark.html)
-for reading and writing ORC files with support for column project and
-predicate push down.
-
 ### [EEL](https://github.com/51zero/eel-sdk)
 
 EEL is a Scala BigData API that supports reading and writing data for
@@ -58,6 +84,14 @@ or directly into Hive tables backed by an ORC file format.
 With more than 300 PB of data, Facebook was an [early adopter of
 ORC](https://code.facebook.com/posts/229861827208629/scaling-the-facebook-data-warehouse-to-300-pb/) and quickly put it into production.
 
+### [LinkedIn](https://linkedin.com)
+
+LinkedIn uses
+[the ORC file format](https://engineering.linkedin.com/blog/2021/fastingest-low-latency-gobblin)
+with Apache Iceberg metadata catalog and Apache Gobblin to provide our data customers with high-query performance.
+
+https://engineering.linkedin.com/blog/2021/fastingest-low-latency-gobblin
+
 ### [Trino (formerly Presto SQL)](https://trino.io/)
 
 The Trino team has done a lot of work [integrating