Data Management and AI: Creating Value at the Edge
By applying edge-specific capabilities and AI integration at the data source, businesses can eliminate inefficiencies, gain greater operational awareness, and …
What’s the Difference Between Streaming Apps and Data-in-Motion?
Many streaming apps use cases help businesses first understand what is going on, and then provide the insights into what to do about
Uber Deploys Exactly-Once Processing System for Ads
Uber's new ad processing system was built with open-source technologies and an innovative exactly-once semantic system for accuracy and
To Batch or To Stream–That Is the Question of the Day
Claypot AI founder, Chip Huyen, designs machine-learning systems that combine streaming data and batch processing to accommodate multiple data
Using Streaming, Pipelining, and Parallelization to Build High Throughput Apps
Streaming, pipelining, and parallelization can be used to design applications to maximize the utilization of resources on a single node. Then, you can add …
Cloud Services for Event-Driven Architectures (EDAs)
The combination of Apache Kafka and Kubernetes helps developers create EDAs and real-time data pipelines that stream and integrate data between
No Time to Waste: 100,000 Messages a Second and Growing
Organizations are using event-driven architectures, Apache Kafka, Apache Pulsar, and other streaming technologies to handle the glut of event messages they …
Linux Foundation to Advance Reactive Programming Using RSocket
RSocket enables long-lived streams of data to be sent across different transport connections. It is especially useful in environments where network connections …
6Q4: Streamlio’s Karthik Ramasamy, on Today’s Stream Processing
Streamlio's co-founder and chief product officer talks about the next generation of stream processing and working with
Data Artisans Aims for Stream Processing at Scale
dA Platform 2 promises centrally managed stream processing capability for enterprises and to manage hundreds of Apache Flink jobs in
