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Exploring Popular Open-source Stream Processing Technologies: Part 1 of 2

A brief demonstration of Apache Spark Structured Streaming, Apache Kafka Streams, Apache Flink, and Apache Pinot with Apache Superset

Gary A. Stafford
ITNEXT
Published in
10 min readSep 24, 2022

According to TechTarget, “Stream processing is a data management technique that involves ingesting a continuous data stream to quickly analyze, filter, transform or enhance the data in real-time. Once processed, the data is passed off to an application, data store, or another stream processing engine.Confluent, a fully-managed Apache Kafka market leader, defines stream processing as “a software paradigm that ingests, processes, and manages continuous streams of data while they’re still in motion.

Batch vs. Stream Processing

Again, according to Confluent, “Batch processing is when the processing and analysis happens on a set of data that have already been stored over a period of time.” A batch processing example might include daily retail sales data, which is aggregated and tabulated nightly after the stores close. Conversely, “streaming data processing happens as the data flows through a system. This results in analysis and reporting of events as it happens.” To use a similar example, instead of nightly batch processing, the streams of sales data are processed, aggregated, and analyzed continuously throughout the day — sales volume, buying trends, inventory levels, and marketing program performance are tracked in real time.

Bounded vs. Unbounded Data

According to Packt Publishing’s book, Learning Apache Apex, “bounded data is finite; it has a beginning and an end. Unbounded data is an ever-growing, essentially infinite data set.” Batch processing is typically performed on bounded data, whereas stream processing is often performed on unbounded data.

Stream Processing Technologies

There are many technologies available to perform stream processing. These include proprietary custom software, commercial off-the-shelf (COTS) software, fully-managed service offerings from Software as a Service (or SaaS) providers, Cloud Solution Providers (CSP), Commercial Open Source Software (COSS) companies, and popular open-source projects from the Apache Software Foundation and Linux Foundation.

Published in ITNEXT

ITNEXT is a platform for IT developers & software engineers to share knowledge, connect, collaborate, learn and experience next-gen technologies.

Written by Gary A. Stafford

Area Principal Solutions Architect @ AWS | 10x AWS Certified Pro | Polyglot Developer | DataOps | GenAI | Technology consultant, writer, and speaker

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