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new 8e5b2760 Add Blurb for Uber blog post (#134)
8e5b2760 is described below
commit 8e5b276071e64320caa112b801689e4e458bd979
Author: Gio <153032991+gio-start...@users.noreply.github.com>
AuthorDate: Wed Sep 4 01:38:35 2024 +0200
Add Blurb for Uber blog post (#134)
* Add Blurb for Uber blog post
* Fix author profile by removing unused content
* Delete data/authors/uber-engineers.mdx
* Update 2024-09-03-pinot-for-low-latency-offline-table-analytics.mdx
* Update 2024-09-03-pinot-for-low-latency-offline-table-analytics.mdx
---------
Co-authored-by: Xiang Fu <xiangfu.1...@gmail.com>
---
data/authors/balci.mdx | 6 ++++++
data/authors/sultana.mdx | 6 ++++++
...not-for-low-latency-offline-table-analytics.mdx | 24 ++++++++++++++++++++++
3 files changed, 36 insertions(+)
diff --git a/data/authors/balci.mdx b/data/authors/balci.mdx
new file mode 100644
index 00000000..246f09bc
--- /dev/null
+++ b/data/authors/balci.mdx
@@ -0,0 +1,6 @@
+---
+name: Caner Balci
+occupation: Software Engineer
+---
+
+Apache Pinot is a real-time distributed online analytical processing (OLAP)
datastore. Use Pinot to ingest and immediately query data from streaming or
batch data sources (including, Apache Kafka, Amazon Kinesis, Hadoop HDFS,
Amazon S3, Azure ADLS, and Google Cloud Storage).
diff --git a/data/authors/sultana.mdx b/data/authors/sultana.mdx
new file mode 100644
index 00000000..d8fd7b51
--- /dev/null
+++ b/data/authors/sultana.mdx
@@ -0,0 +1,6 @@
+---
+name: Ankit Sultana
+occupation: Staff Software Engineer
+---
+
+Apache Pinot is a real-time distributed online analytical processing (OLAP)
datastore. Use Pinot to ingest and immediately query data from streaming or
batch data sources (including, Apache Kafka, Amazon Kinesis, Hadoop HDFS,
Amazon S3, Azure ADLS, and Google Cloud Storage).
diff --git
a/data/blog/2024-09-03-pinot-for-low-latency-offline-table-analytics.mdx
b/data/blog/2024-09-03-pinot-for-low-latency-offline-table-analytics.mdx
new file mode 100644
index 00000000..f23ac7be
--- /dev/null
+++ b/data/blog/2024-09-03-pinot-for-low-latency-offline-table-analytics.mdx
@@ -0,0 +1,24 @@
+---
+title: 'Pinot for Low-Latency Offline Table Analytics'
+date: 2024-09-03
+authors: ['sultana', 'balci', 'uber']
+summary: Apache Pinot™ is a real-time OLAP database capable of ingesting data
from streams like Apache Kafka® and offline data sources like Apache Hive™. At
Uber, Pinot has proven to be really versatile in handling a wide spectrum of
use cases: from real-time use cases with over one million writes per second,
100+ QPS, and <500 ms latency, to use cases which require low-latency analytics
on offline data. Pinot tables fall in three broad categories: real-time,
offline and hybrid. Real-tim [...]
+
+tags:
+ [
+ Pinot,
+ Uber,
+ real-time data platform,
+ Realtime,
+ Analytics,
+ User-Facing Analytics,
+ Elasticsearch,
+ Kafka
+ ]
+---
+
+
+
+Discover how Uber is using Apache Pinot for analysis of offline (batch) data.
With 100+ offline table use cases, and 500+ offline tables, Uber uses an Apache
Spark connector, which supports gRPC streaming, to fetch data from Pinot into
their Hive clusters for an end-to-end streaming architecture.
+
+Read more at [Uber Engineering
Blog](https://www.uber.com/en-PT/blog/pinot-for-low-latency/)
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