by • July 6, 2023
Mainframes continue to play a pivotal role in today’s digital landscape, specifically in large-scale, mission-critical industries such as banking, insurance, healthcare, and government. Their impressive transaction handling capabilities, robust security mechanisms, and efficient resource management make them the go-to choice for organizations dealing with large volumes of sensitive, complex data. Among the numerous databases running on mainframes, DB2 stands out, trusted for decades to store and manage critical data efficiently. However, with the explosion of new technologies and the need for real-time, seamless data flow across disparate systems, a new challenge emerges: how to access mainframe data stored in these DB2 and mainframe databases to the outside world?
The answer lies in the widespread use of REST APIs, which have become the standard protocol for system-to-system communication and data exchange due to their simplicity, statelessness, and platform-agnostic nature.
Here’s the key takeaways from this article:
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The importance of mainframe data cannot be overstated. Mainframes, powered by robust operating systems like z/OS, continue to be the backbone of large-scale, mission-critical industries such as banking, insurance, and government. These mainframes store and manage vast amounts of valuable and complex data that fuels critical business processes. One of the key technologies enabling efficient data management and retrieval from mainframes is Structured Query Language (SQL).
SQL, a powerful and standardized language for managing relational databases, has long been the go-to tool for interacting with mainframe data. Its versatility and flexibility allow organizations to extract meaningful insights, perform complex data analysis, and drive informed decision-making. With SQL, businesses can seamlessly execute queries, retrieve specific data subsets, perform aggregations, and even update or modify records stored within the mainframe database. The familiarity and widespread adoption of SQL make it an invaluable asset for data professionals working with mainframe environments.
To further enhance the efficiency of managing mainframe data, automation plays a crucial role. Automation technologies streamline repetitive and time-consuming tasks, freeing up valuable resources and reducing the risk of errors. With automation, routine activities such as data backups, replication, and data migration between mainframe systems can be performed efficiently and accurately. Automated processes ensure that mainframe data remains consistent, up-to-date, and readily accessible for critical business operations.
By combining SQL-driven data interactions with automation capabilities, organizations can unlock the full potential of their mainframe data. Efficient data management and retrieval allow businesses to gain a competitive edge, improve customer experiences, and drive innovation. Furthermore, the ability to automate various mainframe-related tasks not only saves time and effort but also reduces the risk of manual errors, enhancing overall operational reliability.
Representational State Transfer (REST) APIs have become the cornerstone of modern application architecture. Their simplicity and effectiveness in enabling system-to-system communication have led to their wide acceptance across various sectors.
The adoption of REST APIs is not a random phenomenon; it is backed by several compelling advantages that make them the ideal choice for connecting diverse systems.
One of the most significant benefits of REST APIs is their simplicity. They leverage the existing HTTP protocol, removing the need for complex messaging systems. This simplicity means developers can create, read, update, and delete resources (CRUD operations) using the well-known HTTP methods: GET, POST, PUT, DELETE, making it easier to understand and implement.
Another defining characteristic of REST APIs is their statelessness. Each request from a client to a server must contain all the necessary information to understand and process the request. The server does not store any context between requests, improving reliability and scalability as the server doesn’t need to maintain session information.
REST APIs are platform and language agnostic, making them incredibly versatile. They can serve data in a variety of formats, such as XML or JSON, with JSON being the most popular for its readability and compactness. This language-agnostic nature means that any client that can send HTTP requests and parse JSON or XML can use a REST API, regardless of the programming language, operating system, or platform.
REST services also promote a separation of concerns. The client is not concerned with data storage, and the server does not care about the user interface or user state, resulting in increased modularity and flexibility.
In the context of mainframes and DB2 databases, the universal appeal of REST APIs presents an attractive opportunity. If mainframe data can be exposed via REST APIs, it could be easily ingested and used by any application or system that understands HTTP and JSON or XML, vastly expanding the potential uses of the data trapped within mainframes.
Despite the promising prospect of exposing mainframe data via REST APIs, achieving this goal is not without challenges.
Firstly, there are issues related to data formats and communication protocols. DB2 and other mainframe databases typically use different data models and formats compared to what REST APIs and modern applications expect.
This discrepancy necessitates a conversion process, potentially complex and time-consuming, to transform the mainframe data into a suitable format.
Another challenge is performance degradation. Mainframes are designed to handle an incredible volume of transactions efficiently. However, if REST APIs are not properly implemented and managed, they could become a bottleneck, affecting the overall performance of the system. It is essential to ensure that the process of exposing data through APIs does not inhibit the mainframe’s ability to execute its core tasks.
Data security is another critical concern. Mainframes are known for their robust security mechanisms.
Exposing mainframe data via APIs introduces a new attack vector, potentially exposing sensitive data to unauthorized access or breaches. It is crucial to incorporate robust security measures at the API level to prevent such incidents.
Given these challenges, it’s clear that merely having the desire to expose mainframe data via REST APIs is not enough. What is needed is a comprehensive solution that can not only bridge the gap between mainframes and modern applications but do so in a way that is secure, performant, and efficient.
This is where DreamFactory’s DB2 connectors step in. These connectors allow for the seamless integration of DB2 mainframe data with modern applications via auto-generated REST APIs.
The DB2 connectors work by interpreting the underlying DB2 database schema and automatically generating comprehensive REST endpoints for each table. Once these APIs are set up, they serve mainframe data in formats such as JSON or XML, making the data easily consumable by any application or system that understands HTTP and these formats.
But DreamFactory offers more than just a simple API generation tool. It provides a complete API management solution. This includes robust security measures, such as API key-based authentication, JWT (JSON Web Token), OAuth, LDAP (Lightweight Directory Access Protocol), and SAML (Security Assertion Markup Language) to ensure secure access to your APIs.
Moreover, DreamFactory offers features such as API rate limiting, which prevents any single consumer from overloading the API, and API logging, which provides crucial insights into API usage and performance. API caching is also available to improve response times and reduce server load, and API versioning allows for managing changes and ensuring backward compatibility.
By utilizing DreamFactory’s DB2 connectors, adapters, and the accompanying API management features, developers can overcome the challenges of exposing mainframe data sources through REST APIs, enabling modern applications to easily access and use mainframe data.
The integration of mainframe data sources with modern applications using DreamFactory’s DB2 connectors finds relevance in a wide range of scenarios.
In a banking scenario, for example, a bank may want to create a mobile application that provides real-time access to customer data stored on a DB2 mainframe database. Using DreamFactory’s DB2 connectors, the bank can generate APIs that expose the required data from the DB2 database, providing real-time data access for the mobile app.
Another scenario could be within a healthcare provider wanting to create a unified patient view by integrating data from its mainframe DB2 database and a modern cloud-based Electronic Health Records (EHR) application.
Using DreamFactory’s DB2 connectors, the healthcare provider can generate APIs for both systems, allowing data to flow seamlessly between them, enabling physicians to access comprehensive patient information in real-time, ultimately improving patient care.
In an enterprise scenario, a company could use DreamFactory’s DB2 connectors to integrate mainframe data with modern data analytics tools. By exposing the mainframe data through APIs, the data can be ingested into a data lake for comprehensive analytics, providing the company with valuable insights for data-driven decision making.
Despite their age, mainframes and their DB2 databases continue to play a critical role in today’s business landscape. The rise of REST services presents an opportunity to unlock the vast amounts of data stored in these mainframes, but the path to achieving this is fraught with challenges.
DreamFactory’s DB2 connectors provide a powerful, efficient, and secure solution, enabling the integration of mainframe data with modern applications through auto-generated REST APIs. As the need for seamless data flow continues to grow, the integration capabilities of DreamFactory’s DB2 connectors will only become more valuable and relevant.
Want to know more about how we can help you create, secure and deploy your IBM DB2 API? DreamFactory is an API generation platform that can help your business secure data and get information into the hands of those that need it the most.
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Mainframe data is crucial for large-scale, mission-critical industries like banking and insurance. It fuels critical business processes and stores valuable and complex information.
SQL is a powerful language for managing relational databases, making it the go-to tool for interacting with mainframe data. It allows organizations to extract insights, perform data analysis, and make informed decisions.
Automation streamlines repetitive tasks, such as data backups and replication, reducing errors and freeing up resources. It ensures data consistency, accessibility, and reliability within mainframe systems.
REST APIs are simple, stateless, versatile, and promote separation of concerns. They enable easy system-to-system communication, support various data formats, and enhance modularity and flexibility.
Challenges include data format and communication protocol discrepancies, potential performance degradation, and the need for robust data security measures to protect sensitive information.
DreamFactory’s DB2 connectors seamlessly integrate DB2 mainframe data with modern applications through auto-generated REST APIs. They provide secure access, authentication, rate limiting, logging, caching, and versioning.
Use cases include real-time access to customer data in banking, unified patient views in healthcare, and comprehensive data analytics in enterprises, leveraging DreamFactory’s DB2 connectors.
DreamFactory’s DB2 connectors offer a powerful, efficient, and secure solution, enabling the integration of mainframe data with modern applications. They simplify the process and enhance data flow and accessibility.
Creating an IBM DB2 API in Minutes with DreamFactory
Terence Bennett, General Manager at DreamFactory, has a strong operational, business, and extensive experience in government IT systems and Google Cloud. He started his career as a U.S. Navy Intelligence Officer, then honed his skills on Google’s Red Team and later became the COO of Integrate.io.
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