What is event streaming?
This blog is your go-to guide for understanding event streaming. Discover how it works, why it matters, and how businesses leverage real-time data insights to stay ahead. From real-world applications in industries like finance and healthcare to tools like Apache Kafka.
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Imagine you’re watching your favorite TV series on a streaming platform. Instead of waiting for the entire episode to download, you get to enjoy it as it’s delivered, bit by bit, in real-time. That’s kind of how event streaming works — but instead of videos, it’s streams of data flowing continuously.
So, what is event streaming?
Event streaming is like a live feed of everything happening in your business. An “event” is any action or change — a customer making a purchase, a user clicking a button, or even a sensor recording a temperature. These events are captured and sent to a system that can process them in real-time. Instead of collecting all the data and analyzing it later (like a batch process), event streaming lets you react to what’s happening right now.
Why should we care about it?
Well, imagine being able to spot a fraudulent transaction as it happens or showing a customer the perfect product recommendation based on what they’re browsing at that very moment. Event streaming makes these things possible. It’s fast, efficient, and built for the modern, always-on world we live in.
How does it work?
Events are like cars driving down the road, each carrying some important information. These events are produced by “sources” (like your app, website, or IoT devices) and sent to an event streaming platform. This platform stores the events and allows “consumers” (like your analytics tools or other apps) to read and act on them as they arrive.
What makes event streaming awesome?
Here are a few reasons why businesses are jumping on the event streaming train:
- Real-time insights: Know what’s happening as it’s happening. No more waiting for reports to tell you what’s already old news.
- Scalability: Whether it’s a few events or millions per second, event streaming platforms can handle it.
- Flexibility: Producers (sources) and consumers (apps) are independent. This means you can add or change systems without breaking everything.
- Reliability: Since events are processed individually, one hiccup doesn’t bring the whole system down.
Where can it be used?
Event streaming is transforming how industries operate. Here are just a few examples:
- Energy: Event streaming transforms the energy sector with real-time data for grid management, predictive maintenance, and operational efficiency
- Finance: Detect suspicious transactions the moment they happen to prevent fraud.
- Healthcare: Process patient data from wearable devices instantly to monitor critical conditions.
- Telecom: Spot and fix network issues before they impact customers.
Event streaming related terms
When you dive into event streaming, you’ll often come across a variety of related terms. We know this can feel overwhelming, which is why we’ve simplified some of the most common terms to make them easier to understand.
Kafka Command Line
Apache Kafka offers a command-line interface (CLI) that enables users to interact with Kafka brokers and topics. With the CLI, you can perform essential tasks such as creating, listing, or deleting topics, producing messages to a topic, or consuming messages from a topic. It’s a powerful tool for developers and administrators looking to troubleshoot, test, or monitor Kafka's functionality. Axual Self-Service simplifies Kafka interface management with an intuitive WYSIWYG interface, eliminating the command-line interface (CLI) complexity for a user-friendly experience.
Kafka Bootstrap Server
In Kafka, a bootstrap server serves as the entry point for client applications to connect to a Kafka cluster. It acts as the initial contact point, providing clients with metadata about the Kafka cluster, such as available brokers and partitions. While a single bootstrap server can establish a connection, specifying multiple servers ensures higher reliability. Learn more about Kafka Bootstrap Server and the role in ensuring seamless connectivity.
Kafka Data Pipeline
A Kafka data pipeline allows organizations to process and transport streams of data in real-time. It typically includes producers (data sources), topics (data streams), consumers (applications), and connectors (integrations with external systems). Businesses can create sophisticated workflows that ingest, process, and analyze data continuously. Use cases range from event-driven microservices to real-time analytics and fraud detection.
Kafka Topic: The Backbone of Event Streaming
Kafka topics are the primary abstraction for managing streams of events. A topic is essentially a log where producers write messages, and consumers read from it. Each topic can have multiple partitions, enabling Kafka to scale horizontally and handle high-throughput workloads. Producers can publish events to specific topics, and consumers can subscribe to one or more topics based on their requirements. To better understand Kafka topics and their architecture, explore our blog on Kafka Topics Explained.
What tools are out there?
There are several platforms that help businesses stream events. For example:
- Apache Kafka: A popular open-source tool that’s great for handling massive streams of events.
- Axual: An enterprise Kafka platform specifically designed for Platform and DevOps teams that includes self-service and governance capabilities.
- Confluent: Built on Kafka, it adds extra features to make event streaming even easier for businesses.
- AWS MSK: A fully managed service by AWS for real-time data streaming.
- Apache Pulsar: Another open-source solution that offers multi-tenancy and strong scalability.
- Microsoft Azure Event Hubs: A fully managed event ingestion service that works seamlessly with Azure.
Want to know more about the above streaming systems? We have created a comprehensive event streaming systems overview for you.
Wrapping it up
Event streaming might sound technical, but at its core, it’s about being fast and responsive in a world where things change in an instant. Whether it’s serving customers better, improving operations, or spotting problems before they escalate, event streaming helps businesses stay one step ahead.
If you’re curious about how event streaming could work for you, let’s chat! We’d love to help you get started.
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An event stream is a steady flow of data about changes happening in a system. It includes information about the time and order of events. Anything important for a business to monitor can be part of an event stream. For example, imagine a logistics company tracking the real-time locations of its shipments around the world.
Kafka and Flink are two popular technologies. Apache Kafka is where your event streams are stored. Each event is added to a Kafka topic, where it can be read and used by other systems that need to respond to those events.
The main difference between data streaming and event streaming lies in the type of information being streamed and how it is processed: Data Streaming: This refers to the continuous flow of data in real-time. It involves the transmission of large volumes of data from one point to another, often for analytics, storage, or processing. Data streaming is more focused on the movement of raw data, such as logs, metrics, or sensor readings, and may not always be tied to specific actions or events. Event Streaming: Event streaming, on the other hand, focuses on the streaming of "events" — changes or actions that happen in a system. An event represents a specific occurrence, such as a user making a purchase, a temperature sensor reading, or a transaction being completed. Event streaming systems, like Apache Kafka, capture, store, and process these events in real-time, allowing systems to respond to them instantly.
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