The new Cloudera-Hortonworks Hadoop: 100 percent open source, 50 percent boring
How do you bring Hadoop to the AI, hybrid, and multi cloud era, making it so easy to use and reliable that it's boring? How do you build a sustainable business doing that, while switching to a 100-percent open source model? The new Cloudera raises more questions than it offers answers at this point
Read More →Nvidia GPUs for data science, analytics, and distributed machine learning using Python with Dask
Nvidia wants to extend the success of the GPU beyond graphics and deep learning to the full data science experience. Open source Python library Dask is the key to this.
Read More →Salesforce Research: Knowledge graphs and machine learning to power Einstein
Explainable AI in real life could mean Einstein not just answering your questions, but also providing justification. Advancing the state of the art in natural language processing is done on the intersection of graphs and machine learning.
Read More →A gravitational wave moment for graph. The Year of the Graph Newsletter: March 2019
A gravitational wave moment for the graph community in the W3C Workshop on Web Standardization for Graph Data. Gartner includes Graph as Trend #5 in its Top 10 Data and Analytics Technology Trend for 2019. And graphs continuing to make waves in the real world in every possible way. Read the full article on the […]
Read More →Streamlio, an open-core streaming data fabric for the cloud era
Apache Kafka replacement and beyond. This is open-core Streamlio's claim to fame, and today's announcement of a managed cloud service brings it one step closer to reality.
Read More →Graph data standardization: It’s just a graph, making gravitational waves in the real world
AWS, Google, Neo4j, Oracle. These were just some of the vendors represented in the W3C workshop on web standardization for graph data, and what transcribed is bound to boost adoption of the hottest segment in data management: Graph.
Read More →