Is GraphQL still relevant in 2025?
In 2025, GraphQL remains a strong choice for: Applications requiring dynamic data fetching, such as dashboards or content-driven platforms. Mobile and frontend-heavy applications where minimizing data transfer is critical. Projects that need to unify data from multiple sources or microservices. GraphQL is an open-source query language and server-side runtime that specifies how clients should interact with application programming interfaces (APIs).You should consider using GraphQL if you intend your API to be a NoSQL database. In contrast, consider using SQL if you use a query language to manage your relational database.GraphQL can also act as a middle layer on top of your current systems, giving you a unified way to talk to them. This is handy for adding new features without messing with your old systems.Dgraph is a native GraphQL database with a graph backend. This means Dgraph is not an interface on top of an existing database like Postgres but is actually designed from the ground-up for GraphQL.
Why avoid GraphQL?
Malicious query construction Such queries don’t require resources by the attacker, like a conventional DOS attack would – the idea is the attacker can send a single query that causes a lot of work for the GraphQL server and its upstreams to then resolve. One solution for this is persisted queries. GraphQL requests are sent using the POST HTTP method, but query operations may also be sent using the GET method.Is GraphQL frontend or backend? GraphQL is neither the frontend or backend but rather the language spoken between the two to exchange information.Welcome to GraphQL GraphQL defines a standard grammar for a query language to read/write data. It kind of looks like a neater JSON with just the keys and allows you to pass arbitrary parameters in the query.The usual way, or synchronous GraphQL, deals with requests one at a time. This can make things slow because requests have to wait their turn. Asynchronous GraphQL, on the other hand, can do lots of things at the same time without waiting.Is GraphQL frontend or backend? Both. GraphQL specifies how you can exchange information between client and server.
Is GraphQL just SQL?
Is GraphQL a database language like SQL? No, but this is a common misconception. GraphQL is a specification typically used for remote client-server communications. Unlike SQL, GraphQL is agnostic to the data source(s) used to retrieve data and persist changes. A GraphQL server can process a client query using data from separate sources and present the results in a unified graph. The language is not tied to any specific database or storage engine. There are several open-source runtime engines for GraphQL. Implementations in Java, JavaScript, Ruby, Scala, others.Flexibility: GraphQL enables clients to specify the structure of the response data, avoiding over-fetching or under-fetching issues. With SQL, developers often need to write multiple queries or join statements, which can become cumbersome and inefficient.Graphql is a query language for APIs. It’s just a way for the client to tell server what data it wants and then it is on the server to get the data from its data store to satisfy the client’s requirements. The data store can be relational or nosql dbs. The data returned by graphql is just JSON.Since its inception in 2015, GraphQL has soared in popularity. According to the State of JavaScript 2020 report, it was adopted by 47% of developers in 2020. This includes developers from large companies such as Starbucks, Paypal, and even Facebook.You can use GraphQL and REST APIs interchangeably. However, there are some use cases where one or the other is a better fit. For example, GraphQL is likely a better choice if you have these considerations: You have limited bandwidth, and you want to minimize the number of requests and responses.
What are GraphQL queries?
January 17, 2024. A GraphQL query is a read operation that is used to request specific data from a GraphQL server. It allows clients to specify the exact data they need from an API. GraphQL was developed to fulfill the need for more flexibility and efficiency—to ultimately excel where REST doesn’t. GraphQL solves REST’s weaknesses, especially in data fetching. In this case, you can simply send a single GraphQL query to the server with all the data requirements.REST and GraphQL — Both are powerful, but REST has a slight edge in terms of security due to structural reasons. On the other hand, GraphQL’s flexibility makes it ideal for dynamic applications — but it can be vulnerable without proper security management.So for serving an API for mobile app or react app, it does not matter that one REST endpoint is faster-overall GQL will be much more performant. If you are doing server to server communication then you might look into grpc as well. For server to server there are not many reasons to use Graphql IMHO.Learn how GraphQL resolvers are used to connect to data sources like Amazon DynamoDB, Amazon Aurora, and AWS Lambda. Explore differences in building with a self-managed GraphQL server vs.For simple CRUD operations, GraphQL can feel like overkill compared to REST. Why it matters: More setup: schema, types, resolvers, validation. Harder for small teams or MVPs that just need basic endpoints.
What is GraphQL AEM?
Graphql is designed to evolve with your data so that as additional fields or properties are added, these are in turn exposed via the api. Aem has implemented a set of graphql apis to expose data about content fragments. Content fragments are a way to structure data in aem and is typically object-oriented. Adobe experience manager (aem) is a combined content management system (cms) and digital asset management solution (dam). It helps companies manage and deliver digital files and experiences across various channels, using a range of features including: digital asset management.Robust Integrations One of the most distinguishing features that give AEM an edge over every other CMS platform is its integration. Being a part of the Adobe Marketing Cloud, AEM comes pre-packed with a suite of Adobe marketing tools and software.Overview. AEM Headless is a CMS solution from Experience Manager that allows structured content (Content Fragments) in AEM to be consumed by any app over HTTP using GraphQL. Headless implementations enable delivery of experiences across platforms and channels at scale.HTML Template Language (HTL), supported by Adobe Experience Manager (AEM), aims to provide a highly productive enterprise-level web framework that enhances security. It also enables HTML developers without Java knowledge to participate better in AEM Projects.
Is GraphQL better than REST API?
REST is good for simple data sources where resources are well defined. GraphQL is good for large, complex, and interrelated data sources. REST has multiple endpoints in the form of URLs to define resources. GraphQL has a single URL endpoint. GraphQL APIs can have performance issues, particularly when querying large datasets or when a high number of concurrent requests are made. Developers need to implement strategies like limiting the query depth or ensuring clients are authorized to access only the specific data needed.The following limitations apply for all GraphQL queries: When caching GraphQL queries, the maximum allowed size of a query is 4096 bytes. When caching GraphQL queries, the maximum allowed nesting depth is 10 levels. When processing payload error handling, the maximum allowed size for a response payload is 1024 bytes.Typically, a single, unified GraphQL endpoint per configuration. Multiple endpoints per resource or use case. The client specifies the exact fields needed in the query. The server defines fixed data structure per endpoint.No more than 100 concurrent requests are allowed. This limit is shared across the REST API and GraphQL API. Make too many requests to a single endpoint per minute. No more than 900 points per minute are allowed for REST API endpoints, and no more than 2,000 points per minute are allowed for the GraphQL API endpoint.One of the significant drawbacks to using GraphQL is that it is more difficult to specify the API rate limit than REST. This creates the risk of the cost of queries being unexpectedly large, leading to computation, resource, and infrastructure overload.