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"REST" In Peace: Why GraphQL Is Better Then REST API

Brian DeWyer
Reveille Software

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.

Brian DeWyer is CTO and Co-Founder of Reveille Software

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"REST" In Peace: Why GraphQL Is Better Then REST API

Brian DeWyer
Reveille Software

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.

Brian DeWyer is CTO and Co-Founder of Reveille Software

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The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...