From 64858239d16ce6f8d66f103aa48afa81a65b9bee Mon Sep 17 00:00:00 2001 From: vinoth chandar Date: Wed, 4 Jan 2017 23:58:09 -0800 Subject: [PATCH] Update use_cases.md --- docs/use_cases.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/use_cases.md b/docs/use_cases.md index b0a16ab9e..8e524bf3d 100644 --- a/docs/use_cases.md +++ b/docs/use_cases.md @@ -62,7 +62,7 @@ apply the processing logic, and efficiently update/reconcile late data with a do like 15 mins, and providing an end-end latency of 30 mins at `HD`. -{% include callout.html content="To achieve this, Hoodie borrows concepts from stream processing frameworks like [Spark Streaming](https://spark.apache.org/docs/latest/streaming-programming-guide.html#join-operations) , Pub/Sub systems like [Kafka](http://kafka.apache.org/documentation/#theconsumer) +{% include callout.html content="To achieve this, Hoodie has embraced similar concepts from stream processing frameworks like [Spark Streaming](https://spark.apache.org/docs/latest/streaming-programming-guide.html#join-operations) , Pub/Sub systems like [Kafka](http://kafka.apache.org/documentation/#theconsumer) or database replication technologies like [Oracle XStream](https://docs.oracle.com/cd/E11882_01/server.112/e16545/xstrm_cncpt.htm#XSTRM187). For the more curious, a more detailed explanation of the benefits of Incremetal Processing (compared to Stream Processing & Batch Processing) can be found [here](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop)" type="info" %}