Data Applications Guide

Apache Spark is a real-time data processing system with support for diverse data sources and programming styles.

Platform as a service (PaaS) is a cloud computing model where third-party providers provide a software and/or hardware platform to users in the cloud.

SQL development tools and capabilities play a big role in data application development. However, developers should choose the tools in their toolbox wisely

Event-driven architecture (EDA) is a software design pattern for application development. It allows organizations to track and detect “events” and then instantly act on these events.

Data streaming is the ongoing transfer of data at a high rate of speed. Most data streams are continuously collecting data from thousands of data sources.

Parquet is an open source file format built to handle flat columnar storage data formats.

Embedded analytics integrates data insights within the context of business applications, providing visualizations directly into workflows.

PySpark is the Python API that supports Apache Spark. Apache Spark is a open-source, distributed framework that is built to handle Big Data analysis.

What use cases are a good fit for the Spark framework? Here are a few scenarios where using Spark makes sense: