The Kafka-Spark-Cassandra pipeline has proved popular because Kafka scales easily to a big firehose of incoming events, to the order of 100,000/second and
Topic: Apache Hadoop and Spark
Apache Hadoop, Spark and Kafka.
As Oracle recounts, Apache Spark excels at running machine learning queries on massive data
A 55-page report on the state of enterprise Hadoop adoption, including vendors, use cases, and
A data lake needs to be fed and governed properly before analytics can discover kernels of
Running Spark on the mainframe can be advantageous because data is co-located. One use is fraud
Telecoms have valuable real-time data they can sell for urban planning. The challenge: build a platform to analyze
Data governance and metadata synchronization can prevent Hadoop data from going dark.
“When we look at what's behind the dynamic growth in the big data arena, right now we see it at Apache
Modern data warehouse design often involves new platforms that can deal with new sources of unstructured and real-time data, as well as use of
Apache Spark offers fast speeds, integration with a variety of programming languages, and flexibility. But Spark vs. Hadoop MapReduce is not an either-or