Modernizing Infrastructures for Fast Data with Spark, Kafka, Cassandra, Reactive Platform and Mesos
Why it's time to modernize your infrastructure for 'data in motion'View on Slideshare
The Big Data industry emerged in response to the unprecedented sizes of data sets collected by Internet companies and the particular needs they had to store and use that data. Today, the need to process that data more quickly is morphing Big Data architectures into Fast Data architectures.
In this session, Dean Wampler, Big Data Architect at Lightbend, presents the forces driving this trend and the most popular tools that have emerged to address particular design challenges:
- Spark - For sophisticated processing of data streams, as well as traditional batch-mode processing.
- Kafka - For durable and scalable ingestion and distribution of data streams.
- Cassandra - For scalable, flexible persistence.
- Reactive Platform: Lagom, Akka, and Play - For integration of other components and building microservices.
- Mesos - For cluster resource management.
Missed the webinar? Watch it here!Watch on YouTube
Learn more about Fast Data
For a deeper look at the technologies powering 'data in motion', we have some great learning opportunities prepared. As we mentioned on our blog, you can potentially meet Dean when he delivers a session on Scala and Data Science at GOTO Chicago in late May. But, if you cannot make it there, we suggest you download Dean's white paper Fast Data: Big Data Evolved to learn more about this trend.