Apache flink use cases. Let’s .

Apache flink use cases. For more examples, please see the Powered by Flink page. Jan 14, 2025 · Learn when to use Apache Flink for stateless stream processing and ETL, its SaaS benefits, and when to use Kafka Streams or Connect's SMT. Uber Use Case Nov 8, 2023 · Generative AI (GenAI) enables advanced AI use cases and innovation but also changes how the enterprise architecture looks like. Spark is best in batch processing and helps multiple languages, catering to various use cases. Explore key differences in architecture and use cases. Apache Flink use The Apache Flink SQL Cookbook is a curated collection of examples, patterns, and use cases of Apache Flink SQL. May 8, 2023 · TLDR Dive into a comprehensive comparison of Apache Flink and Apache Spark, exploring their differences and strengths in data processing, to help you decide which framework best suits your data processing needs. By seamlessly integrating stream and batch processing capabilities, Apache Flink caters to diverse data processing needs, from continuous data streaming to large-scale batch computations. udemy. 5+ million fixed customers. They help businesses build systems that are ready for the future. Apache Flink Use Cases and features May 15, 2024 · On the other hand, Apache Flink offers a more expressive and flexible API, especially for advanced use cases involving state manipulation and complex event processing. Aug 9, 2024 · Compare Apache Flink and Spark in terms of architecture, features, performance, and use cases. Many of the recipes are completely self-contained and can be run in Ververica Platform as is. This tutorial will brief about the various diverse big data use cases where the industry is using different Big Data tools (like Hadoop, Spark, Flink, etc. 12, the Stream processing engines like Apache Flink are commonly used for simple data processing tasks like moving real-time streaming data into a database. g. Oct 17, 2024 · High Throughput and Low Latency: Designed for real-time data applications, Flink’s architecture is optimized for both high throughput and low-latency processing, making it suitable for demanding use cases like fraud detection, anomaly detection, and recommendation engines. , Kafka) in Jun 3, 2024 · Discover how Flink Use Cases can drive real-time success for your business. 1: Case Study of a Fraud Detection System January 15, 2020 - Alexander Fedulov (@alex_fedulov) In this series of blog posts you will learn about three powerful Flink patterns for building streaming applications: Dynamic updates of application logic Dynamic data partitioning (shuffle), controlled at runtime Low latency alerting based on custom windowing Aug 25, 2023 · Here are the top 10 use cases of Apache Flink: Real-Time Analytics: Flink excels at processing and analyzing streaming data in real time, making it ideal for scenarios that require immediate insights from data as it arrives. This can lead to developers Oct 3, 2023 · It is linearly scalable and can reach a throughput of 10 million records per second in some use cases. Apr 4, 2025 · Apache Flink 2. Flink-Doris-Connector: With built-in Flink CDC, this Connector ingests data from OLTP databases to Doris. Flink offers low-latency and stateful computations, enabling users to process live data and generate insights on-the-fly. Event-Driven Applications The Event-driven Application takes the events as input and performs computations, state updates, and external actions. The checkpoint coordinator synchronously triggers both pipeline operators and The document discusses Apache Flink, emphasizing its transition from batch to streaming analytics, which is driven by the need for real-time data processing in various industries. Jun 13, 2024 · PyFlink — A Simple Use Case in Data Analytics Introduction Apache Flink is an open-source stream-processing framework that provides powerful capabilities for processing both batch and stream Apr 14, 2025 · For example, an agent might use LangChain for planning or decision logic within a single task, while Apache Kafka and Apache Flink handle the real-time flow of events, coordination between agents, persistence, and system-level guarantees. Jun 28, 2024 · As a result, data streaming with Apache Kafka and Apache Flink makes the market clearer, speeds up information sharing, and improves forecasting and risk management. So far, we have realized auto-synchronization of data from MySQL and Oracle to Doris. Jan 3, 2023 · This is the first post of the series that shows building operational use cases with Apache Kafka and Apache Flink. alto and Powerledger. Many business use cases cannot wait for a user to prompt them into action. Real-world use cases for Flink AI model inference Fraud detection in financial services: Banks and payment processors use remote model inference with Flink to analyze transaction data in real time. Jan 15, 2020 · Advanced Flink Application Patterns Vol. Aug 14, 2024 · Atomicity Guarantees Stream processors that also handle batches require strong consistency guarantees to ensure distributed transactions process accurately in case of failure. com/course/apache-f Apache Flink, Apache Hadoop, HDFS, Apache YARN,Mongodb,Big Data, Remore Oct 25, 2023 · This article explores the integration of Apache Kafka, Flink, and Druid as the real-time data architecture for a wide range of streaming data use cases. Feather: C++, Python, R Feb 10, 2025 · Discover how Apache Flink powers real-time analytics in travel and hospitality, enhancing customer experience, security, and efficiency. Additionally, it explores real-world use cases across sectors like VERA-X: Introducing the First Native Vectorized Apache Flink® Engine Redefining Speed and Efficiency in Apache Flink with VERA-X Apache Flink® is the standard for Feb 5, 2025 · New eBook: The Ultimate Data Streaming Guide: Concepts, Use Cases and Success Stories with Apache Kafka and Flink. Flink: Discover Apache Flink, a fast and reliable stream processing framework. Discover the key differences between Apache Flink and Apache Kafka, prominent players in data stream processing. Flink's Flink Use Cases To demonstrate how Flink can be applied to unbounded datasets, here’s a selection of real-word Flink users and problems they’re solving with Flink. Jul 23, 2024 · Architecture Design While Apache Spark and Apache Flink both support processing real-time data, they do so in fundamentally different ways. Find out how this open-source platform enables fault-tolerant stream processing and batch analytics. Amazon Managed Service for Apache Flink is a fully managed service that allows you to build and run applications that use Apache Flink - an open-source framework and engine for processing big data streams - without the need for infrastructure management. Here, we present Flink’s easy-to-use and expressive APIs and libraries. Let’s Oct 15, 2025 · Why Apache Flink Agents Matters # While AI agents have made rapid progress in interactive applications like chatbots and copilots, these systems typically operate in synchronous, one-off interactions. Use Cases Here are some example applications of the Apache Arrow format and libraries. Learn which framework suits your real-time or batch processing needs. Processors, analytics, storage and other components are included to build a real-time data pipeline. However, for high-value, revenue-generating and cost-reduction-oriented real-time use cases such as personalized recommendations and fraud detection, additional distinct components are needed in your technology stack. In conclusion, mastering real-time pipelines with Apache Flink involves understanding its core capabilities and applying best practices to harness its full potential. The following are some of the use cases of Apache Flink. Jul 23, 2025 · Flink applications are fault-tolerant in the case of a machine failure and use exactly-once semantics. More Flink users are listed in the Powered by Flink directory in the project wiki. Flink also provides a range of programming language support, including Python, Java, and SQL. On this page, we present a few notable Flink users that run interesting use cases in production and link to resources that discuss their applications in more detail. Apr 14, 2024 · Apache Flink comes with four different APIs, each of which performs a multitude of different actions and allows for many different use cases, as they are highly customisable. Apache Flink − Bouygues Telecom Bouygues Telecom is one of the largest telecom organization in France. Apache Flink use In this tutorial, we will talk about real-life case studies of Big data, Hadoop, Apache Spark and Apache Flink. Note that Flink’s Table and The Apache Flink® Table API offers a high-level, relational API for both stream and batch processing, blending the DataStream API's power with the SQL API's simplicity, in Java or Python. Aug 1, 2024 · By using Flink’s unified architecture, developers can build and maintain a single application to handle both use cases, reducing complexity and ensuring consistency in data processing logic. Apache Flink Use Cases and features May 20, 2023 · We will also go through common Flink use cases in data engineering, such as real-time data streaming, complicated event processing, and machine learning. Apache Flink is a versatile tool capable of handling a wide variety of use cases in the realm of data processing. Jan 16, 2023 · Apache Flink and Apache Airflow are both open-source tools for data processing, but they have different primary use cases and functionality. These differences are due in large part to their origin and primary use cases. Under each are linked several examples, mostly from the Flink Forward conference. With Flink 1. Building Blocks for Streaming Applications The types of applications that can be built with and executed by a Feb 27, 2024 · 3 dynamic use cases for Apache Flink and stream processing feature Feb 27, 2024 6 mins Analytics Development Libraries and Frameworks Open Source Aug 8, 2024 · The advanced features of Apache Flink enable organizations to handle real-time data streams with unparalleled efficiency and accuracy. Data Pipelines & ETL # One very common use case for Apache Flink is to implement ETL (extract, transform, load) pipelines that take data from one or more sources, perform some transformations and/or enrichments, and then store the results somewhere. Jul 23, 2025 · Must Read: Top 10 Trends on Big Data Analytics 7 Interesting Open Source Projects using Big Data Conclusion In conclusion, Apache Spark and Apache Flink stand out as effective distributed data processing frameworks with different strengths. Below, we explore the most common types of applications that are powered by Flink and give pointers to real-world examples. The three layers of API are Process Functions (also known as the Stateful Stream Processing API), DataStream, and Table and SQL. In this chapter, we will understand a few test cases in Apache Flink. Jun 4, 2025 · Learn more about Apache Flink: real-time processing, benefits, use cases, and how to outperform other Big Data platforms. Sep 22, 2024 · Complete Example of Flink Usage in a Project Use Case: Real-Time User Behavior Analytics In this example, we use Apache Flink to process user activity logs from a streaming source (e. To demonstrate how Flink can be applied to unbounded datasets, here’s a selection of real-word Flink users and problems they’re solving with Flink. Conversely, Flink shows prowess in stream processing Data Pipelines & ETL # One very common use case for Apache Flink is to implement ETL (extract, transform, load) pipelines that take data from one or more sources, perform some transformations and/or enrichments, and then store the results somewhere. Discover the key differences between apache nifi vs apache flink and determine which is best for your project. In this article, we will explore the key concepts and techniques involved in performing real-time ETL with Apache Flink in the context of Big Data. Let’s delve into some fundamental scenarios where Apache Flink See full list on data-flair. Data streaming with Apache Kafka and Apache Flink provides the foundation for scalability, security, and real-time analytics that modern financial services demand. Feb 12, 2024 · Community Use Cases Real-world Examples of Apache Kafka® and Flink® in Action. Its ability to handle both streaming and batch data shines through in diverse scenarios, allowing organizations to extract actionable insights in real time. While traditional databases, data lakes, and warehouses are effective for many batch-based use cases, they fall short in scenarios demanding low latency, scalability, and real-time decision-making. Oct 22, 2025 · Remote model inference with Apache Flink for AI and GenAI use cases provides a scalable, flexible and resilient approach to making data-driven decisions. My Journey With Kafka And Flink Nov 23, 2024 · Here is very simple java code for Apache flink using Pattern API to detect a fraud case like account take over, after detecting a series of event Let’s setup first Maven dependencies: Apache Flink documentation provides comprehensive guides and resources for stateful computations over data streams using the Flink framework. Blink adds a series of improvements and integrations (see the Readme for details), many of which fall into the category of improved bounded-data/batch processing and SQL. Apache Flink takes raw events and processes them, making them more relevant in the broader business context. Sep 14, 2023 · The main differences between Apache Spark and Apache Flink are in their architecture, programming model, and use cases. It highlights key differentiators of Flink, such as low latency, high throughput, and its ability to ensure accurate results even during failures. As the project evolved to address specific uses cases, different core APIs ended up being implemented for batch (DataSet API) and streaming execution (DataStream API), but the higher-level Table API/SQL was subsequently designed following this mantra of unification. It excels at real-time stream processing and supports both bounded and unbounded data streams. This blog post explores the use cases and architectures for scalable and reliable real-time energy trading, including real-world deployments from Uniper, re. Optimize resource allocation: Properly allocate memory and CPU resources to Flink jobs to ensure optimal performance. While both are designed to handle big data workloads, they have distinct architectures, processing models, and use cases. Using Flink and Kafka in your data plan makes things more efficient. Powered By Flink # Apache Flink powers business-critical applications in many companies and enterprises around the globe. One thing Apache Flink: Features, Benefits, and Use Cases Features of Apache Flink Apache Flink stands out due to its robust set of features that cater to the needs of modern data processing. Here are some of the key features that make Flink a preferred choice: Stream Processing: Flink is designed to process data streams in real-time, making it ideal for applications that require immediate insights Jul 28, 2023 · Apache Flink offers layered APIs that offer different levels of expressiveness and control and are designed to target different types of use cases. For more, see our blog and the list of projects powered by Arrow. What is Apache Flink ? Feb 20, 2025 · Apache Spark and Apache Flink are two of the most popular open-source frameworks for large-scale data processing. Apache Flink is a framework for stateful computations over unbounded and bounded data streams. Are you looking for a powerful tool to process real-time data? Look no further than Apache Flink! This open-source framework is designed to handle large-scale data processing with ease, making it a popular choice for businesses of all sizes. This post explores the key concepts of stateless and stateful stream processing, using Kafka Streams and Apache Flink as May 26, 2023 · Understand its role as a highly efficient message queue and data streaming platform. Event-driven Applications, e. Use Cases | Latest news and updates about stream processing with Apache Flink and Unified Streaming Data Platform. Dec 20, 2024 · Apache Flink and Apache Spark are both distributed data processing frameworks, but they have distinct characteristics, use cases, and approaches to stream and batch processing. The lines are also blurring between the two as hybrid engines capable of micro-batch stream processing emerge. Nov 28, 2023 · Apache Flink stands as a robust stream processing framework, offering a myriad of applications across diverse use cases. Jun 5, 2025 · This blog explores capabilities, use cases, and integration of durable execution engines with data streaming technologies like Apache Kafka, Flink and Spark Structured Streaming—highlighting their potential to create scalable, resilient architectures for modern distributed enterprise systems. Flink provides multiple APIs at different levels of abstraction and offers dedicated libraries for common use cases. By delivering Apache Flink® as a Platform-as-a-Service offering to its internal development teams, ONEU optimizes the deployment and management of Flink applications, ultimately supporting real-time fraud detection for millions of financial transactions daily. During event processing, events are combined, aggregated and enriched, providing deeper insights and enabling many types of use cases, such as: Feb 9, 2025 · The ability to process massive amounts of financial data instantly is no longer optional—it’s a competitive necessity for operational and analytical use cases. Hear from the experts in the Community about how they are using Data in Motion to thrive in the world of digitization, emerge competitively stronger and unlock new ways of how you operate. What are event-driven applications? Apache Flink can be used for multiple stream processing use cases. It also encourages new ideas. Since then they have been using Flink for multiple use Apache Flink can easily scale up to many cores system and provides very high throughput and at the same time low latency. Spark uses a batch processing model, while Flink uses a data streaming model. In this article, we'll explore the top five use cases for Flink in real-time data processing. Think advertising, stocks/trading, performance monitoring and such real time use cases. Data streaming with Apache Kafka and Apache Flink processes incoming data sets in real-time at scale, connects various platforms, and Jun 3, 2024 · By delving into the architectural nuances, use case implications, and performance benchmarks of Apache Spark versus Apache Flink, organizations can make informed decisions regarding their big data infrastructure choices. Note that Flink’s Table and https://www. We will delve into how Flink’s stream processing model can be used to handle the complexities of continuous data processing, ensure data quality, and enable businesses to derive valuable insights from their data streams with low latency. Outline Introduction to Apache Flink and Apache Spark Comparison of key features Performance benchmarks and scalability Recommendations for choosing the right tool for specific use Jan 6, 2025 · Any application that need to consume and produce "events" would be very adorable use case for flink. Comparing Apache Flink with Other Big Data Frameworks Common Use Cases for Apache Flink Apache Flink is widely used in a variety of real-time data processing scenarios, including: ELT and ETL data pipelines Flink enables continuous ELT and ETL pipelines, moving and optionally transforming data between systems in real-time. Reading/writing columnar storage formats Many Arrow libraries provide convenient methods for reading and writing columnar file formats, including the Arrow IPC file format ("Feather") and the Apache Parquet format. In the first two parts of our Inside Flink blog series, we explored the benefits of stream processing with Flink and common Flink use cases for which teams are choosing to leverage the popular framework to unlock the full potential of streaming. Specifically, we broke down the key reasons why developers are choosing Apache Flink® as their stream processing framework, as well as the ways in Jun 26, 2025 · Nifi vs Flink: Compare Apache NiFi and Apache Flink for real-time data processing. LangChain and similar toolkits help define how an agent thinks. Please note that the list Jul 27, 2025 · Apache Flink is an open-source framework for Stateful stream processing at scale. In this tutorial, we will talk about real-life case studies of Big data, Hadoop, Apache Spark and Apache Flink. Aug 8, 2024 · Apache Flink is an open-source framework designed for large-scale data processing. The framework is fault-tolerant and scalable, making it suitable for various use cases. Oct 16, 2025 · Discover Apache Flink, explore how it differs from other tools such as Kafka and Spark, and the benefits and challenges of using it. Bouygues heard about Apache Flink for the first time in a Hadoop Group Meeting held at Paris. Apr 25, 2024 · Apache Flink was central in facilitating these capabilities, especially in event-driven decisions, which found immediate applications across various teams within Lyft, including a project to revamp Lyft’s Traffic infrastructure using real-time data aggregation. In this post we show how developers can use Flink to build real-time applications, run analytical workloads or build real-time pipelines. Learn what Apache Flink is, and understand its features, architecture, and use cases. Apache Flink is an open source software technology for running stateful computations on both streaming data and batch data in a distributed system. This article explores their roles, features, use cases, advantages and how they synergize when combined, offering insights for real-time analytics, data handling, and machine learning. In this article we will dissect what Flink is, what its components are, how it works, and most importantly – why you should consider using it. ProjectPro's apache nifi and apache flink comparison guide has got you covered! Mar 11, 2021 · Flink has been following the mantra that Batch is a Special Case of Streaming since the very early days. training Nov 29, 2022 · Apache Flink is a powerful open-source streaming data processing platform. Oct 28, 2024 · Flink was originally built for streaming use cases but has become robust for batch workflows as well. ) to solve the specific problems. This combo boosts performance and scalability, making data-driven decisions easier. What are the common use cases for Apache Flink? Flink comes with pre-defined window assigners for the most common use Feb 16, 2024 · Looking to see how other companies are using Kafka? Apache has some real business use cases here. 1. 0 enables real-time data processing with enhanced scalability, stream analytics, and AI-driven insights for faster decisions. Conclusion Apache Flink and Apache Kafka together make a strong team for real-time apps. Explore the benefits of Apache Flink for instant data processing. Apache Flink can handle real-time data pipelines. . With Amazon Managed Service for Apache Flink, you can transform and analyze streaming data in real time using Oct 2, 2023 · The documentation for Flink lays out three distinct use cases for Flink. Large Language Models (LLM), Vector Databases, and Retrieval Augmentation Generation (RAG) require new data integration patterns. Download now for free. By leveraging Flink's robust features for use cases like real-time analytics, fraud detection, and ETL processes, businesses can achieve a competitive edge in today's fast-paced data-driven landscape. Apache Flink comes with four different APIs, each of which performs a multitude of different actions and allows for many different use cases, as they are highly customisable. Feb 13, 2019 · Enter Blink Blink is a fork of Apache Flink, originally created inside Alibaba to improve Flink’s behavior for internal use cases. Oct 31, 2023 · Flink use cases Circling back to the three broad categories of streaming use cases introduced at the beginning of this article, let’s see how they map onto what you’ve just been learning about Apache Spark vs Flink—detailed comparison of architecture, performance, ecosystem, ease of use in data processing—and more! With the combination of Apache Flink and Apache Kafka, the open-source event streaming possibilities become exponential. Mar 19, 2024 · Flink is also fully integrated with Confluent’s tooling for security, governance and observability. Latest news and updates about stream processing with Apache Flink and Unified Streaming Data Platform. Aug 15, 2024 · Yahoo benchmarked the cost and performance for two specific use cases on self-managed Apache Flink and Google Cloud Dataflow. In industrial settings such as e-commerce, finance, IoT, and logistics, critical decisions must be made instantly in Sep 25, 2020 · What does processwindowfunction do in Apache Flink? A ProcessWindowFunction gets an Iterable containing all the elements of the window, and a Context object with access to time and state information, which enables it to provide more flexibility than other window functions. Advantages of Apache Kafka Apache Flink has a distributed architecture which makes it scalable. Apache Flink use cases include: Fraud detection, anomaly detection, rule-based alerting, real-time UX personalization are examples of use cases for event-driven application. Dec 27, 2024 · The rise of stream processing has changed how we handle and act on data. Second, Apache Flink comes with four different APIs, each tailored to different users and use cases. It has 11+ million mobile subscribers and 2. Learn from the real case studies how to solve problems related to Big Data. As Flink streams transaction details, it makes API calls to a centralized fraud detection model, which returns a risk score for each transaction. Understand your use case: Tailor your Flink configuration and deployment to the specific needs of your application. In this section we are going to look at how to use Flink’s DataStream API to implement this kind of application. Again Flink uses some unique techniques: Two-phase commits – Flink‘s lightweight transactions commit results atomically across jobs. Apache Flink also meets data processing requirements, does so at scale, in a streaming manner and within Confluent’s offering. Apache NiFi materials will note that ETL functions can be offloaded into Apache NiFi but this isn’t always appropriate for Confluent use cases. bkzuhwf tbj nqwc bqnu0q xupf tbtqk bfq xsigx 3bd1s ikrk