Data streaming is a new software category to process data in motion. Apache Kafka is the de facto standard used by over 100,000 organizations. Plenty of vendors offer Kafka platforms and cloud services. Many complementary stream processing engines like Apache Flink and SaaS offerings have emerged. And competitive technologies like Pulsar and Redpanda try to get market share. This blog post explores the data streaming landscape of 2023 to summarize existing solutions and market trends.
Apache Hadoop is getting more and more relevant. Not just for big data processing (e.g. MapReduce), but also in fast data processing (e.g. stream processing). Recently, I published two blog posts on the TIBCO blog to show how you can leverage TIBCO BusinessWorks 6 and TIBCO StreamBase to realize big data and fast data Hadoop use cases.
Slides from my talk “Hadoop and Data Warehouse (DWH) – Friends, Enemies or Profiteers? What about Real Time?”…
Slides from my session “Big Data beyond Apache Hadoop – How to Integrate ALL your Data” at JavaOne 2013 in San Francisco are online.
Slides from my talk “Big Data beyond Apache Hadoop – How to integrate ALL your data” at NoSQLmatters 2013 in Cologne are online.
In March 2013, I was at 33rd Degree – “A Conference for Java Masters”. I had two talks, including a new one: “You are not Facebook or Google? Why you should still care about Big Data”. It is a great talk to give an overview about big data, especially from a business perspective (paradigm shift, business value, challenges). However, I also talk about alternatives for big data from a technology perspective, mainly about the defacto standard Apache Hadoop, its ecosystem, distributions, and tooling (i.e. big data suites).