If you’ve ever wondered what Apache Kafka is and you really don’t know very well how you could get the most out of this solution, in this article We’re going to review some real use cases, where companies from different vertical markets have managed to solve complex problems with their data.
Contenidos del Artículo
Introduction
Apache Kafka is a data streaming platform. Provides messaging queue management, data integration and data processing capabilities for millions of messages (or events) per second, continuous data updates for mission-critical workloads, and adaptability with cloud environments are part of its characteristics.
In this video, which has two chapters, I show you how to install and configure step-by-step an Apache Kafka instance on MS Windows. In the second part of the video, I show you how Kafka can be integrated with Change Data Capture solutions to accelerate data capture processes from databases in real time (This video is in Spanish, make sure to enable English captions).
Apache Kafka in Financial and Insurance Industry
Fraud Detection
Fraud is a multi-billion dollar business and is increasing every year, especially with the addition of cryptocurrencies. The global economic crime and fraud survey conducted in 2022 by PWC shows that 52% of companies with 10B profits have been affected by a fraud incident.
Specifically in the financial sector, we must deal with a high and constant volume of fraud, illicit transactions, and money laundering. This situation is a major threat to customers of online banking services, in addition to having an impact on small businesses, as they face losses when they are victims of cyber-attacks or illicit transactions.
With Apache Kafka, financial institutions can effectively detect fraud and therefore restore their integrity, ensuring the best security measures for their customers. Apache’s platform will allow systems to independently learn behavioral patterns by scanning large data volumes. Once transactional trends are understood, it is easy to detect fraudulent transactions.
Here are some examples of financial institutions that adopted Apache Kafka in their systems:
The Evolution of Kafka at ING Bank
Marching Toward a Trillion Kafka Messages per Day: Running Kafka at scale at PayPal
Transaction processing in Real Time
Using Apache Kafka in real-time transaction processing offers a few benefits that are critical to the efficiency and effectiveness of financial systems and other applications that require low latency and high availability. Here are some of the main benefits:
Horizontal Scalability
Apache Kafka allows you to scale horizontally to handle large volumes of transactions in real time. You can distribute topic partitions on different nodes to improve processing capacity.
Low Latency
Kafka is designed to provide low latency, meaning transactions can be transmitted and processed in real time, crucial for financial applications that require fast responses.
Durability and Fault Tolerance
Apache Kafka stores data durably and offers fault tolerance. This ensures that transactions are not lost, even in situations of temporary outages or node failures.
Integration of Heterogeneous Systems
Kafka makes it easy to integrate heterogeneous systems. You can connect applications written in different languages and run on different platforms, simplifying the architecture of complex systems.
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Real-Time Data Flow
It enables real-time data transmission and processing, which is essential for financial applications that need to react instantly to market events, detect fraud, or perform real-time risk analysis.
Handling Large Volumes of Data
Kafka is efficient at handling large volumes of data. This is critical in financial environments where the number of transactions can be massive.
Data Reprocessing
Allows reprocessing of historical data. If there are changes to processing logic or new applications are introduced, Kafka provides the ability to reprocess stored data.
Decoupling of Producers and Consumers
Kafka decouples data producers from consumers, meaning that applications can evolve independently without affecting other parts of the system. This facilitates the maintainability and flexibility of the system.
Facilitates Building Microservices
Apache Kafka serves as a key component in building microservices architectures, enabling communication and data transmission between services efficiently.
Monitoring and Metrics
It offers built-in tools and metrics to monitor system performance, making it easy to detect and resolve problems in real time.
Data Persistence and Retention
Apache Kafka allows data retention for a configurable period, facilitating historical analysis and auditing.
These benefits make Apache Kafka a robust choice for real-time transaction processing, providing a robust and scalable infrastructure for financial and other similar applications.
Other Activities where Apache Kafka can Support Financial Operations
Customer Data Management
Financial companies use Apache Kafka to integrate customer data scattered across different systems. This allows a unified customers view, improving services personalization and offering a more complete experience.
Risk Analysis
Apache Kafka is used to transmit data to real-time analytics platforms. This is essential to proactively assess and manage financial risks, identifying patterns and behaviors that could indicate potential risks.
Market Event Processing
For financial institutions, it is crucial to stay on top of market events in real time. Apache Kafka facilitates business data transmission and processing, allowing an informed and faster decision making.
Order Management and Execution
Kafka is used to transmit data related to order management and execution in real time. This is essential for algorithmic trading platforms and order execution systems that require low latency and high availability.
Continue reading: Setting Clear Objectives and Goals for Data Management Projects
Monitoring of Financial Transactions
Transactions traceability is essential in the financial sector. Apache Kafka helps in building distributed transaction logging systems, ensuring integrity, and tracking of transactions across different systems.
Application and Microservices Integration
In a complex financial environment, where various applications and microservices interact, Apache Kafka acts as a centralized channel for communication between these components, facilitating integration and efficient communication.
These examples illustrate how Apache Kafka has become an essential tool for addressing specific challenges and realizing opportunities in the financial industry, providing a robust infrastructure for real-time data management.