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new ea916c1700 Docs: Update vendor information for Cloudera (#10278)
ea916c1700 is described below
commit ea916c1700ef37377d3e8bba1197b3fe32d1a248
Author: Andrew Sherman <[email protected]>
AuthorDate: Tue May 14 00:40:09 2024 -0700
Docs: Update vendor information for Cloudera (#10278)
---
site/docs/vendors.md | 25 ++++++++++++++++---------
1 file changed, 16 insertions(+), 9 deletions(-)
diff --git a/site/docs/vendors.md b/site/docs/vendors.md
index 5b8e1a76a1..dc20783da5 100644
--- a/site/docs/vendors.md
+++ b/site/docs/vendors.md
@@ -33,15 +33,22 @@ ClickHouse is a column-oriented database that enables its
users to generate powe
### [Cloudera](http://cloudera.com)
-Cloudera Data Platform integrates Apache Iceberg to the following components:
-* Apache Hive, Apache Impala, and Apache Spark to query Apache Iceberg tables
-* Cloudera Data Warehouse service providing access to Apache Iceberg tables
through Apache Hive and Apache Impala
-* Cloudera Data Engineering service providing access to Apache Iceberg tables
through Apache Spark
-* The CDP Shared Data Experience (SDX) provides compliance and self-service
data access for Apache Iceberg tables
-* Hive metastore, which plays a lightweight role in providing the Iceberg
Catalog
-* Data Visualization to visualize data stored in Apache Iceberg
-
-https://docs.cloudera.com/cdp-public-cloud/cloud/cdp-iceberg/topics/iceberg-in-cdp.html
+[Cloudera's data
lakehouse](https://www.cloudera.com/products/open-data-lakehouse.html)
+enables customers to store and manage their data in open table
+formats like Apache Iceberg for running large scale multi-function analytics
and AI.
+Organizations rely on Cloudera's Iceberg support because it is easy to use,
easy
+to integrate into any data ecosystem and easy to run multiple engines - both
Cloudera
+and non-Cloudera, regardless of where the data resides.
+It provides a common standard for all data with unified security, governance,
metadata
+management, and fine-grained access control across the data.
+
+[Cloudera](https://www.cloudera.com/) provides an integrated end to end open
data lakehouse with the ability
+to ingest batch and streaming data using NiFi, Flink and Kafka, then process
+the same copy of data using Spark and run analytics or AI with our
+[Data
Visualization](https://www.cloudera.com/products/cloudera-data-platform/data-visualization.html),
+[Data warehouse](https://www.cloudera.com/products/data-warehouse.html) and
+[Machine Learning](https://www.cloudera.com/products/machine-learning.html)
tools on private
+or any public cloud.
### [Dremio](https://www.dremio.com/)
