Middleware is a type of messaging that simplifies integration between applications and systems. Learn how middleware works, its benefits, use cases, and common solutions.
Middleware refers to software that sits between different applications or components to facilitate communication, data exchange, and other interactions. It typically isn’t software that users ever see; instead, it's part of the software infrastructure layer that runs in the background. Middleware abstracts into common interfaces the different and often unique aspects of underlying database, networking, and other infrastructure functions, making it easier for business-level apps to share their own data and functions, and leverage those of other apps.
Middleware can be thought of as a system of highways with on-ramps and exits that connects applications, databases, and other enterprise IT infrastructure, allowing them to communicate in a predictable, performant, and extensive way.
Middleware reduces the time, cost, and risk of connecting and integrating a business application into an Enterprise’s existing data and network infrastructure. Because it manages these flows of data, messages, and functions, it can also bring additional benefits around performance, scalability, security, and other important characteristics of the typically complex modern enterprise architecture.
Here are the top benefits of middleware:
Middleware acts as a bridge, integrating diverse technologies, tools, and databases, enabling a unified service for its users. Applications, data sources, and other infrastructure can rely on common interfaces to communicate with each other and share data in a predictable and systematic way. New enterprise requirements can be implemented by integrating with standard existing applications and services, instead of custom implementation.
Middleware provides a faster, easier way of connecting applications into your existing infrastructure, helping to simply complex, modern enterprise architectures. The use of common interfaces reduces the need to write, test, and integrate custom code on a one-off basis for each additional data source, sink, or service provider. This reduces the cost and risk associated with development time and operations, and increases velocity.
Middleware, in its connective role, can optimize access to data, scale up or down processing across multiple servers or services as required, and handle failures.
As a centralized service, Middleware can enforce authentication, authorization, encryption, policy, and logging as imposed by the business of the enterprise.
In the 80s, developers created middleware abstractions to connect disparate applications and systems running in different environments. It eliminated the need to write individual pieces of code to make all the systems talk to each other. Since then, middleware has evolved to the point that it has become a vital part of the modern software development process and has reduced the overall development burden. Especially for distributed systems where components run on different servers (or even different data centers), middleware eliminates some of the communications challenges related to integrating software components and systems. These benefits allow developers to focus on the core application logic rather than trying to figure out the underlying infrastructure.
Middleware applications span a wide range of industries and use cases, each designed to solve specific challenges.
Here are some of the most common types of middleware and how they are used in the wild:
Middleware is commonly used for event-driven architectures, real-time analytics, and IoT applications. Examples include Apache Kafka®, RabbitMQ, and IBM MQ. Middleware can also route messages between different systems and applications for complex workflows and provides a centralized point of control for message routing, such as for Enterprise Service Bus (ESB)-based architectures. Examples Microsoft BizTalk Server, Oracle Service Bus, and Red Hat Fuse.
Middleware can connect and integrate ERP, CRM, and supply chain management systems. Examples include data integration platforms like MuleSoft Anypoint Platform, Oracle Fusion Middleware, and Red Hat JBoss.
Middleware can orchestrate access to an enterprise’s data assets stored in databases and stores, such as Microsoft SQL Server, Oracle Database, PostgreSQL, or Apache Hadoop. Middleware can also support and implement specific business semantics; examples include those found in Vertical industries, such as in the finance, healthcare, and telecommunications.
Middleware can ensure secure communications and implement policies for the protection of sensitive data, through encryption, authentication, authorization, and access control and tracking. Examples include IBM Security Access Manager, Ping Identity, and Symantec Secure Site.
Middleware exposes APIs to external systems and applications to enable third-party integration, or provides a self-service interface for internal systems. For example, in healthcare, middleware can expose APIs for patient data, so third-party developers can build applications that securely access the data.
Middleware functions can include the management of host web applications, enterprise applications, and other software services. Examples include Apache Tomcat, IBM WebSphere Application Server, and Oracle WebLogic Server.
Middleware functionality can include the content management and delivery across publishing, media, and e-commerce platforms. Examples include Adobe Experience Manager, Drupal, and Sitecore.
Apache Kafka is a distributed streaming platform that is designed to handle large volumes of data in real-time. Originally created at LinkedIn, it’s now an open-source project maintained by the Apache Software Foundation.
At a high level, Kafka provides a publish-subscribe messaging system that allows different applications and services to communicate with each other in real-time. Producers can send messages to one or more topics, and Consumers can subscribe to those topics to receive messages in real-time. Kafka also provides libraries for stream processing for more sophisticated data or event processing.
Kafka is designed to be highly scalable, fault-tolerant, and distributed. Kafka's architecture allows it to handle millions of messages per second with low latency, and support complex data processing workflows, making it suitable for real-time data processing and streaming applications in a decoupled way, on-premise, in a cloud, or in hybrid configurations. This makes it ideal as the backbone for a Middleware-based enterprise architecture, or to support specific sub-scenarios, such as message brokering, event streaming, real-time data processing, log aggregation.
Confluent is a data streaming platform that helps businesses implement real-time data streaming services.
Based on Apache Kafka, Confluent extends Kafka with additional features, such as a centralized control plane for managing and monitoring Kafka clusters, 120+ connectors and integrations to connect Kafka with other applications, and schema management. These features enable businesses to access, store, and manage data more easily as continuous, real-time streams.
The founders, who also created Kafka, designed Confluent as a unified platform that allows businesses to capture data in real-time data and use it to affect business decisions. A huge problem that plagues modern data architectures is that data is distributed across multiple applications and generated and consumed in real time. Hence, businesses need help leveraging this data when making decisions. Confluent can help.
In conjunction with Kafka as the messaging middleware, businesses can use Confluent to: