In the JVS low-code development platform, there is a capability that allows for quick echoing of multiple data entries by ...

Typically, most applications consist of both batch and online workloads. This is true even today, when most of our attention has turned to online and web-based interaction. Sure, online activities are ...

Batch processing, a long-established model, involves accumulating data and processing it in periodic batches upon receiving user query requests. Stream processing, on the other hand, continuously ...

At QCon NY, Shriya Arora presented “Personalising Netflix with Streaming Datasets” and discussed a migration of a data processing job from batch-style ETL to stream processing using Apache Flink.

In this manner, Lambda satisfied the data processing needs for a certain class of applications that valued high-throughput, low-latency, fault-tolerance, and data accuracy. Many organizations—in ...

Legacy systems weren’t built for today’s demands, but banks don’t have the luxury of rip and replace. Learn how one bank ...

This is where batch processing comes up short. Our survey revealed that 99% of respondents think it's important to process and act on data as quickly as possible.

In batch processing, if costs are not isolated, high-volume customers and products tend to subsidize lower-volume ones. This article reviews different types of batch activities and how they would be ...

Between Process Data Servers three and four is a Microsoft SQL data base server that stores batch-related data collected by Process Data Servers 3 and 4. Connected to each pair of Process Data Servers ...

Streaming data records are typically small, measured in mere kilobytes, but the stream often goes on and on without ever stopping. Streaming data, also called event stream processing, is usually ...