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new 2e33071 Add Data Mechanics to Powered By
2e33071 is described below
commit 2e330710c855f4292cc066c60874a32385a60fb6
Author: Jean-Yves Stephan <jean-y...@datamechanics.co>
AuthorDate: Wed Nov 18 12:54:59 2020 -0600
Add Data Mechanics to Powered By
Data Mechanics is a managed Spark platform that can be deployed on a
Kubernetes cluster inside our customers cloud accounts. We'd love to be on the
Powered By Spark page (along other Spark platforms).
We contribute to open source projets in the Spark ecosystem (Spark on
Kubernetes operator, Data Mechanics Delight). We also use Spark internally for
our recommendation engine and logs processing.
I tried to be objective / avoid marketing in the description, but I'm open
to feedback on changing it. Thanks!
Author: Jean-Yves Stephan <jean-y...@datamechanics.co>
Closes #299 from jystephan/datamechanics-poweredby.
---
powered-by.md | 6 ++++++
site/powered-by.html | 9 +++++++++
2 files changed, 15 insertions(+)
diff --git a/powered-by.md b/powered-by.md
index 150d402..d314c88 100644
--- a/powered-by.md
+++ b/powered-by.md
@@ -88,6 +88,12 @@ and external data sources, driving holistic and actionable
insights.
- We provided a <a href="https://www.databricks.com/product";>cloud-optimized
platform</a>
to run Spark and ML applications on Amazon Web Services and Azure, as well
as a comprehensive
<a href="https://databricks.com/training";>training program</a>.
+- <a href="https://www.datamechanics.co";>Data Mechanics</a>
+ - Data Mechanics is a cloud-native Spark platform that can be deployed on a
Kubernetes cluster
+ inside its customers AWS, GCP, or Azure cloud environments.
+ - Our focus is to make Spark easy-to-use and cost-effective for data
engineering workloads.
+ We also develop the free, cross-platform, and partially open-source Spark
monitoring tool
+ <a href="https://www.datamechanics.co/delight";>Data Mechanics Delight.</a>
- <a href="https://datapipelines.com";>Data Pipelines</a>
- Build and schedule ETL pipelines step-by-step via a simple no-code UI.
- <a href="http://dianping.com";>Dianping.com</a>
diff --git a/site/powered-by.html b/site/powered-by.html
index b12cf5f..8b93aaa 100644
--- a/site/powered-by.html
+++ b/site/powered-by.html
@@ -321,6 +321,15 @@ to run Spark and ML applications on Amazon Web Services
and Azure, as well as a
<a href="https://databricks.com/training";>training program</a>.</li>
</ul>
</li>
+ <li><a href="https://www.datamechanics.co";>Data Mechanics</a>
+ <ul>
+ <li>Data Mechanics is a cloud-native Spark platform that can be deployed
on a Kubernetes cluster
+inside its customers AWS, GCP, or Azure cloud environments.</li>
+ <li>Our focus is to make Spark easy-to-use and cost-effective for data
engineering workloads.
+We also develop the free, cross-platform, and partially open-source Spark
monitoring tool
+<a href="https://www.datamechanics.co/delight";>Data Mechanics Delight.</a></li>
+ </ul>
+ </li>
<li><a href="https://datapipelines.com";>Data Pipelines</a>
<ul>
<li>Build and schedule ETL pipelines step-by-step via a simple no-code
UI.</li>
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