Many organizations rely on enterprise content systems to deliver their information efficiently. However, these content services (heavy applications) must integrate with various applications and services to ensure smooth operation. This integration is not an afterthought; it's a critical component for enabling consistency, collaboration, and streamlining the entire data interaction process. And with no-code/low-code themes in Robotic Process Automation (RPA) and Intelligent Automation product sets typically seen in modern content services applications, less is more to accelerate solution delivery.
To accomplish application integrations, IT developers will increasingly have a choice between GraphQL and REST APIs for web client interfaces. Facebook developed GraphQL, now an open-source query language and runtime for APIs. By contrast, Representational State Transfer Application Programming Interface, or REST API, is an architectural style for network application design.
But which one is better? Spoiler alert: it's GraphQL, and here's why ...
REST API Limitations
REST API is a set of rules that enable communication between different software applications over the internet and is widely used for web services and integration purposes. The software offers simplicity, scalability and is platform-independent. However, these advantages come with notable drawbacks. Among these drawbacks are:
■ Over-fetching and under-fetching data. The over-fetching limitation promotes wasted bandwidth and processing resources, while under-fetching causes additional data requests because all the requested information is unavailable in a single REST endpoint request.
■ Multiple round trips. Frequently REST APIs require multiple trips to the server to retrieve data. The yo-yo activity increases latency, impacts response times, and hampers the efficiency of content retrieval operations.
■ Lack of flexibility in data retrieval and manipulation. Traditional APIs usually expose predefined endpoints and fixed data structures, limiting the flexibility for retrieving and manipulating content. This lack of flexibility poses challenges when specific data needs or transformations arise.
■ Architecture limitations. There are no standards for the implementation of REST APIs. Traditional APIs are often built on monolithic architectures, where all functionalities and data access are tightly coupled. This restricts the ability to scale and evolve individual components independently, hindering agility and innovation.
GraphicQL, The Clear Choice
Compared to REST APIs, GraphQL offers a more efficient approach to specifying and retrieving data without all the wasted network resources and bandwidth. GraphicQL emerges as the clear winner for these reasons:
■ Efficient and precise queries. The most noticeable difference between GraphQL and REST API is that GraphQL eliminates the problem of over-fetching or under-fetching data. Clients can retrieve multiple resources and their associated fields in a single request.
■ Strong typing system. GraphQL defines data structures and their relationships better than REST APIs. Using a type system that defines the capabilities of the API, GraphQL allows clients to validate the correctness of their queries, ensures that clients receive the expected data shape, and helps prevent runtime errors.
■ Single endpoint. GraphQL typically exposes a single endpoint, meaning clients don't need to make multiple requests to different endpoints for data searches. This simplifies the client-side implementation and reduces the number of network requests needed to retrieve data.
■ Ecosystem and tooling. Because it's an open-source option, GraphQL has a growing ecosystem with various tools and libraries for different programming languages and frameworks. These tools provide developers with helpful features such as code generation, schema stitching, caching, and debugging.
No More Resting On Your Laurels REST API
Enterprise data and its associated relationships are getting more complex every day. The increased complexity means that enterprise content management applications must improve data retrieval, performance and establish a seamless integration with other systems.
GraphQL emerges as a better choice for content management over REST API in a side-by-side comparison. The efficiency, flexibility, and enhanced developer experience provided by GraphQL displays the clear advantages of efficiency, flexibility, and improved developer experience. That's why GraphQL is the recommended development API for IBM FileNet applications. When it comes to harnessing the complete capabilities of content systems, GraphQL gives a competitive edge in the content management landscape.
The Latest
In MEAN TIME TO INSIGHT Episode 6, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network automation ...
In the ever-evolving landscape of software development and infrastructure management, observability stands as a crucial pillar. Among its fundamental components lies log collection ... However, traditional methods of log collection have faced challenges, especially in high-volume and dynamic environments. Enter eBPF, a groundbreaking technology ...
Businesses are dazzled by the promise of generative AI, as it touts the capability to increase productivity and efficiency, cut costs, and provide competitive advantages. With more and more generative AI options available today, businesses are now investigating how to convert the AI promise into profit. One way businesses are looking to do this is by using AI to improve personalized customer engagement ...
In the fast-evolving realm of cloud computing, where innovation collides with fiscal responsibility, the Flexera 2024 State of the Cloud Report illuminates the challenges and triumphs shaping the digital landscape ... At the forefront of this year's findings is the resounding chorus of organizations grappling with cloud costs ...
Government agencies are transforming to improve the digital experience for employees and citizens, allowing them to achieve key goals, including unleashing staff productivity, recruiting and retaining talent in the public sector, and delivering on the mission, according to the Global Digital Employee Experience (DEX) Survey from Riverbed ...
App sprawl has been a concern for technologists for some time, but it has never presented such a challenge as now. As organizations move to implement generative AI into their applications, it's only going to become more complex ... Observability is a necessary component for understanding the vast amounts of complex data within AI-infused applications, and it must be the centerpiece of an app- and data-centric strategy to truly manage app sprawl ...
Fundamentally, investments in digital transformation — often an amorphous budget category for enterprises — have not yielded their anticipated productivity and value ... In the wake of the tsunami of money thrown at digital transformation, most businesses don't actually know what technology they've acquired, or the extent of it, and how it's being used, which is directly tied to how people do their jobs. Now, AI transformation represents the biggest change management challenge organizations will face in the next one to two years ...
As businesses focus more and more on uncovering new ways to unlock the value of their data, generative AI (GenAI) is presenting some new opportunities to do so, particularly when it comes to data management and how organizations collect, process, analyze, and derive insights from their assets. In the near future, I expect to see six key ways in which GenAI will reshape our current data management landscape ...
The rise of AI is ushering in a new disrupt-or-die era. "Data-ready enterprises that connect and unify broad structured and unstructured data sets into an intelligent data infrastructure are best positioned to win in the age of AI ...
A majority (61%) of organizations are forced to evolve or rethink their data and analytics (D&A) operating model because of the impact of disruptive artificial intelligence (AI) technologies, according to a new Gartner survey ...
