{"id":3965,"date":"2025-02-24T13:45:23","date_gmt":"2025-02-24T13:45:23","guid":{"rendered":"https:\/\/devsite.qyrus.com\/qapi\/?p=3965"},"modified":"2025-02-24T13:51:54","modified_gmt":"2025-02-24T13:51:54","slug":"what-is-the-difference-between-soap-vs-rest-vs-graphql-vs-streams","status":"publish","type":"post","link":"https:\/\/devsite.qyrus.com\/qapi\/what-is-the-difference-between-soap-vs-rest-vs-graphql-vs-streams\/","title":{"rendered":"What is the difference between SOAP vs REST vs GraphQL vs Streams? Which API approach is right?"},"content":{"rendered":"\t\t
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You\u2019re spending a lot of time testing APIs and under different conditions. With every test you run, the success rate you achieve, there are some learnings along the way that make you realize lot more than you usually account for.\u00a0<\/p>

Consider a rapidly growing company working towards refining its digital infrastructure. Their engineering team must make an important decision, on picking the API strategy that supports expansion while maintaining performance and flexibility.\u00a0\u00a0<\/p>

REST has been the industry-standard for long, but GraphQL is gaining traction for its precise data-fetching capabilities. SOAP, though considered legacy, remains the backbone of industries like banking and healthcare due to its reliability and security. Meanwhile, event-driven architectures, powered by Streams, are transforming real-time data processing.\u00a0<\/p>

The Challenge?<\/strong>\u00a0<\/p>

Each approach has trade-offs\u2014REST is simple but can often exposure to multiple inefficiencies in data retrieval. GraphQL offers flexibility but adds complexity, SOAP on the other hand ensures strict compliance but feels rigid in modern agile environments. And Streams enable real-time interactions but requires long list of efforts to make a shift in system design. Organizations must make these choices wisely, to balance performance, security, and scalability.\u00a0<\/p>

API testing differs from the tasks you need to execute<\/b> to validate functionality and performance, rather than just verifying outputs. It involves understanding the nuances of data transmission, error handling, and system interactions, helping you refine your approach to scalable testing and automation.\u00a0<\/p>

Learn about the four popular API paradigms\u2014REST API<\/b>, SOAP<\/b>, GraphQL<\/b>, and Streams <\/b>\u2014to you developers and testers understand their relevance, functionality, and when to use them. By the end, you\u2019ll have a clearer picture of which API approach aligns best with your product, your users, and your long-term vision. Let\u2019s dive in.<\/strong>\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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What are REST, GraphQL, Streams and SOAP?\u00a0<\/strong><\/h4>

All these are different types of APIs each created to serve a unique proposition and use case. From building the right mobile application to integrating microservices, having the right API architecture in place makes all the difference.\u00a0<\/p>

At a time where code makes or breaks a product it\u2019s important to know what they are, what they can do before you figure out how to use them.\u00a0<\/p>

  1. What is REST API (Representational State Transfer)<\/b>\u00a0<\/li><\/ol>

    REST API is an architectural template introduced in the 2000s built to be easy to use and implement<\/b>. It uses the standard HTTP methods (GET, POST, PUT, DELETE) to interact with resources and design networked applications.\u00a0<\/p>

    REST APIs support caching mechanisms (via HTTP headers like Cache-Control<\/b> and ETag<\/b>) to reduce the load on the server. And majorly use JSON or XML for data exchange.\u00a0<\/p>

    The reason why it\u2019s used widely is REST\u2019s stateless nature making it a good fit for applications that need to grow and handle high traffic.<\/b>\u00a0<\/p>

    Ideal use case<\/b>: Web and mobile apps, public APIs, microservices.\u00a0<\/p>

    Example<\/b>: You can search the user data from a server using a GET request to\u202f\/users\/1.\u00a0<\/p>

    How does a REST API work:<\/b> REST APIs uses standard HTTP methods to execute CRUD (Create, Read, Update, Delete) operations. Here each request is stateless, as it contains all necessary information for processing, and responses are in JSON or XML format.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    What is SOAP (Simple Object Access Protocol)\u00a0<\/b>\u00a0<\/h3>

    SOAP was introduced in the late 1990s and is one of the oldest protocols used for exchanging structured information in distributed systems. The intent was to design and establish strict standards for enterprise-level communication.\u00a0<\/p>

    SOAP has advantages in industries that need high security and reliability, such as banking, healthcare, and government entities. The rigid structure on SOAP provides consistency and compliance with standards like WS-Security.\u00a0<\/p>

    Ideal Use Case<\/b>: Enterprise applications, financial transactions, legacy systems.\u00a0<\/p>

    Example<\/b>: You can create a SOAP request to a banking service to initiate transfer funds:\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    How does SOAP API work:<\/b> SOAP operates on an\u00a0 XML-based messaging format and requires a strong protocol specification. It supports ACID* transactions, built-in error handling, and enterprise-grade security features.\u00a0<\/p>

    SOAP Uses WSDL (Web Services Description Language)<\/b> for defining operations.\u00a0<\/p>

    *FYI- ACID stands for Atomicity, Consistency, Isolation, and Durability<\/b>\u2014it\u2019s a set of features that help maintain data integrity, especially in enterprise applications dealing with sensitive or financial data.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    What is GraphQL\u00a0<\/b>\u00a0<\/h3>

    GraphQL was developed and launched in the market by Facebook in 2015 to address inefficiencies that were found in the REST APIs, aiming to solve issues related to over-fetching and under-fetching of data. It helped users to request exactly what they needed, while eliminating the need for unnecessary data transfer.\u00a0<\/p>

    GraphQL\u00a0 grew its popularity in mobile and web applications as the need for dynamic data requirements were crucial in these segments. It\u2019s ideally useful for complex queries and real-time updates.\u00a0<\/p>

    You can easily use a single endpoint<\/b> (\/graphql) instead of multiple routes.\u00a0<\/p>

    For example<\/b>: A user can write a request to server for a user\u2019s name and email:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    How does GraphQL work:<\/strong> GraphQL enables clients to request precisely the data they need through a structured query language. Instead of multiple API calls, clients can send a single query specifying exactly what they need.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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    Streams<\/b>\u00a0<\/p>

    Streams were developed as a resource to handle continuous data flow in real-time for applications. As traditional APIs operated on request-response models, Streams are capable of enabling constant data transmission within separate systems.\u00a0<\/p>

    Streams pushes data to clients as it becomes available. It\u2019s put into action by using technologies like WebSockets, Server-Sent Events (SSE), Kafka, or gRPC Streams<\/b>.\u00a0<\/p>

    How does streams work?<\/b>\u00a0<\/p>

    1. Connection Established<\/b> \u2013 The client subscribes to a data stream using protocols like WebSockets, Server-Sent Events (SSE), or Kafka<\/b>.\u00a0<\/li>
    2. Continuous Data Flow<\/b> \u2013 Once connected, the server pushes data<\/b> to the client in real time whenever new data is available.\u00a0<\/li>
    3. Event-Driven Updates<\/b> \u2013 The stream automatically updates the client when new information arrives, eliminating the need for repeated API requests (polling).\u00a0<\/li>
    4. Handling & Processing<\/b> \u2013 The client processes incoming data immediately, whether it’s a stock price update, chat message, or live sensor data.\u00a0<\/li>
    5. Closing the Stream<\/b> \u2013 When no longer needed, the client or server can terminate<\/b> the connection to stop the data flow.\u00a0<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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      Now you might get confused as even GraphQL has the same functionality, but the difference lies in the approach.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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      Key Differences Between GraphQL and Streams\u00a0<\/h4>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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      \n
                   Feature<\/b>\n <\/div>\n <\/td>\n
      		GraphQL<\/b>\n <\/td>\n Streams<\/b>\n <\/td>\n <\/tr>\n <\/thead>\n
      Underlying Mechanism<\/span> <\/span>\n <\/td>\n Built on <\/span>WebSockets<\/span><\/span> to push updates from the server when data changes.<\/span> <\/span>\n <\/td>\n Uses <\/span>various streaming protocols<\/span> like <\/span>WebSockets<\/span>, SSE, Kafka, or <\/span>gRPC<\/span> for continuous or event-driven data transmission.<\/span><\/span> <\/span>\n <\/td>\n <\/tr>\n
      Data Flow<\/span> <\/span>\n <\/td>\n Clients subscribe to specific changes (e.g., updates to a particular entity).<\/span> <\/span>\n <\/td>\n Data flows <\/span>continuously<\/span> (like a live feed) or <\/span>is pushed<\/span> based on events.<\/span><\/span> \n<\/span>\n <\/td>\n <\/tr>\n
      Use Case<\/span> <\/span>\n <\/td>\n Best for applications where clients need to get <\/span>real-time updates on specific queries<\/span> (e.g., chat apps, stock price updates).<\/span> <\/span>\n <\/td>\n Ideal for <\/span>high-throughput, event-driven, or real-time streaming<\/span> use cases (e.g., video streaming, IoT, analytics pipelines).<\/span> <\/span>\n <\/td>\n <\/tr>\n
      Scalability<\/span> <\/span>\n <\/td>\n Can be complex to scale due to WebSocket limitations. Requires <\/span>additional<\/span> infrastructure for large-scale deployments.<\/span><\/span> <\/span>\n <\/td>\n Designed for <\/span>high-scale<\/span> real-time processing (e.g., Kafka <\/span>handles<\/span> millions of messages per second).<\/span><\/span> <\/span>\n <\/td>\n <\/tr>\n
      State Management<\/span> <\/span>\n <\/td>\n Works well for structured, <\/span>stateful<\/span> real-time updates.<\/span> <\/span>\n <\/td>\n Works for both <\/span>stateful and stateless<\/span> event-driven architectures.<\/span> <\/span>\n <\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n<\/div>\n \t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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      When to use SOAP vs REST vs GraphQL vs Streams?<\/strong>\u00a0<\/p>

      When should you use REST API:<\/b>\u00a0<\/p>

      1. When you are building scalable web applications that require stateless communication.\u00a0<\/li>
      2. For public-facing APIs used for third-party integrations.\u00a0<\/li>
      3. Applications that will benefit from caching mechanisms for performance optimization.\u00a0<\/li><\/ol>

        Example:<\/b> Social media platforms like Twitter<\/b> use REST APIs for fetching tweets, posting updates, and managing user profiles.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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        When should you use SOAP:<\/b>\u00a0<\/p>

        1. Enterprise-level applications that need high security along compliance.\u00a0<\/li>
        2. For building systems handling financial transactions or sensitive data.\u00a0<\/li>
        3. And also, legacy systems that need to abide by well-defined standards.\u00a0<\/li><\/ol>

          Example:<\/b> Payment gateways like PayPal<\/b> heavily use SOAP APIs to secure money transactions, ensuring integrity and security.\u00a0<\/p>

          When should you use GraphQL:<\/b>\u00a0<\/p>

          1. For mobile and web applications that require efficient data fetching with minimal over-fetching\/under-fetching.\u00a0<\/li>
          2. Complex queries involving nested relationships across multiple entities.\u00a0<\/li>
          3. If you need real-time visibility through dashboards and personalized content delivery.\u00a0<\/li><\/ol>

            Example:<\/b> GitHub<\/b> uses GraphQL APIs to allow developers to fetch repository details, issues, and pull requests in a single query, improving efficiency.\u00a0<\/p>

            When should you use Streams:<\/b>\u00a0<\/p>

            1. For real-time monitoring systems, such as IoT sensors and stock market applications.\u00a0<\/li>
            2. Event-driven architectures like chat applications or live notifications.\u00a0<\/li>
            3. To build and manage big data pipelines that need continuous processing.\u00a0<\/li><\/ol>

              Example:<\/b> Netflix<\/b> leverages streaming APIs to deliver video content in real-time, ensuring seamless playback and adaptive streaming.\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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              \n <\/td>\n               		REST<\/td>\n SOAP<\/td>\n GraphQL<\/td>\n Streams<\/td>\n <\/tr>\n <\/thead>\n
              Design<\/span> <\/span>\n <\/td>\n Exposes data\/resources via URIs. Focuses on CRUD operations (Create, Read, Update, <\/span>Delete<\/span>).<\/span><\/span> <\/span>\n <\/td>\n Exposes operations (functions or actions) via a strict contract. Focuses on service actions.<\/span> <\/span>\n <\/td>\n Exposes a flexible query system that allows clients to request exactly the data they need.<\/span> <\/span>\n <\/td>\n Exposes a continuous stream of events or data, often in real-time, through a persistent connection.<\/span> <\/span>\n <\/td>\n <\/tr>\n
              Transport Protocol<\/span> <\/span>\n <\/td>\n HTTP\/HTTPS<\/span> <\/span>\n <\/td>\n HTTP\/HTTPS, SMTP, JMS, <\/span>etc.<\/span><\/span> <\/span>\n <\/td>\n HTTP\/HTTPS<\/span> <\/span>\n <\/td>\n WebSockets<\/span>, HTTP\/2, MQTT, <\/span>gRPC<\/span><\/span> <\/span>\n <\/td>\n <\/tr>\n
              Data Format<\/span> <\/span>\n <\/td>\n Typically,<\/span> JSON or XML<\/span><\/span> <\/span>\n <\/td>\n XML<\/span> <\/span>\n <\/td>\n JSON (typically)<\/span> <\/span>\n <\/td>\n Varies (JSON, Avro, <\/span>Protobuf<\/span>, <\/span>etc.<\/span>)<\/span><\/span> <\/span>\n <\/td>\n <\/tr>\n
              Performance<\/span> <\/span>\n <\/td>\n Generally fast<\/span>, lightweight, stateless, scalable.<\/span><\/span> <\/span>\n <\/td>\n Slower due to XML parsing and overhead.<\/span> <\/span>\n <\/td>\n Can be efficient but depends on query design (over-fetching, under-fetching).<\/span> <\/span>\n <\/td>\n High performance for real-time, but latency can vary based on connection.<\/span> <\/span>\n <\/td>\n <\/tr>\n
              Scalability<\/span> <\/span>\n <\/td>\n Easily scalable with caching and load balancing.<\/span> <\/span>\n <\/td>\n Less scalable due to heavier processing overhead.<\/span> <\/span>\n <\/td>\n Highly scalable with efficient query design.<\/span> <\/span>\n <\/td>\n Highly scalable, especially in real-time environments.<\/span> <\/span>\n <\/td>\n <\/tr>\n
              Security<\/span> <\/span>\n <\/td>\n Typically relies on HTTPS, <\/span>OAuth, and API keys.<\/span><\/span> <\/span>\n <\/td>\n Built-in WS-Security, SSL, <\/span>and <\/span>additional<\/span> standards.<\/span><\/span> <\/span>\n <\/td>\n Relies on HTTPS, <\/span>OAuth, and custom access control.<\/span><\/span> <\/span>\n <\/td>\n Security relies on the transport <\/span>layer (e.g., SSL\/TLS).<\/span><\/span> <\/span>\n <\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n<\/div>\n \t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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              How to handle these APIs under different conditions<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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              REST API Testing Best Practices:<\/b>\u00a0<\/h3>

              Validate Endpoint Configurations:<\/b>\u00a0<\/p>

              1. Ensure that all API routes are correctly defined with the proper URL structures.\u00a0<\/li>
              2. Check for missing or misconfigured routes, which can result in broken functionality or unexpected failures during API calls.\u00a0<\/li><\/ol>

                Ensure Correct HTTP Status Codes:<\/b>\u00a0<\/p>

                1. Verify that the API returns the appropriate HTTP status codes for different scenarios (e.g., 200 OK for successful requests, 400 Bad Request for client-side errors, 500 Internal Server Error for server-side issues).\u00a0<\/li>
                2. Incorrect status codes can cause misinterpretations by the client and complicate debugging.\u00a0<\/li><\/ol>

                  Implement Efficient Caching:<\/b>\u00a0<\/p>

                  1. Test caching mechanisms to ensure reduced database load and optimized response times.\u00a0<\/li>
                  2. Ensure cache invalidation is handled properly, preventing unnecessary data retrievals from the database on repeated requests.\u00a0<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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                    SOAP API Testing Best Practices:<\/b>\u00a0<\/h3>

                    XML Schema Validation:<\/b>\u00a0<\/p>

                    1. Confirm that XML requests and responses conform to the defined XSD schema.\u00a0<\/li>
                    2. Validate the presence and correctness of required fields in the XML payloads to avoid parsing errors.\u00a0<\/li><\/ol>

                      Verify Required Headers:<\/b>\u00a0<\/p>

                      1. Ensure that essential headers, such as authentication tokens and content-type metadata, are properly included in API requests.\u00a0<\/li>
                      2. Missing headers can result in authentication failures, permission issues, or malformed requests.\u00a0<\/li><\/ol>

                        Test for Security Flaws:<\/b>\u00a0<\/p>

                        1. Perform security testing to identify weak encryption protocols, inadequate input sanitization, or improper authorization checks.\u00a0<\/li>
                        2. Ensure sensitive data is transmitted securely and that access control mechanisms are strictly enforced.\u00a0<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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                          GraphQL API Testing Best Practices:<\/b>\u00a0<\/h3>

                          Test for Efficient Query Handling:<\/b>\u00a0<\/p>

                          1. Ensure the server can efficiently handle deeply nested queries without triggering performance bottlenecks, such as high CPU usage or timeouts.\u00a0<\/li>
                          2. Test for graceful handling of complex queries to prevent server crashes under heavy loads.\u00a0<\/li><\/ol>

                            Validate Resolver Logic and Data Integrity:<\/b>\u00a0<\/p>

                            1. Test resolver functions to ensure they return correct and complete data according to the schema, preventing data inconsistencies or incomplete responses.\u00a0<\/li><\/ol>

                              Optimize Query Efficiency:<\/b>\u00a0<\/p>

                              1. Design queries to avoid over-fetching (retrieving excessive data) or under-fetching (missing essential data) from the server.\u00a0<\/li>
                              2. Monitor and optimize response payload sizes to maintain performance and reduce the client-side processing burden.\u00a0<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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                                Streams API Testing Best Practices:<\/b>\u00a0<\/h3>

                                Check Connection Stability:<\/b>\u00a0<\/p>

                                1. Test how the stream handles persistent connections under high network traffic or fluctuating network conditions.\u00a0<\/li>
                                2. Ensure that connection dropouts or instability don\u2019t interfere with the real-time data flow.\u00a0<\/li><\/ol>

                                  Avoid Duplicate Event Handling:<\/b>\u00a0<\/p>

                                  1. Test the system\u2019s ability to handle and de-duplicate events in the message stream to prevent data inconsistencies and avoid redundant processing.\u00a0<\/li><\/ol>

                                    Minimize Latency:<\/b>\u00a0<\/p>

                                    1. Measure the latency in real-time data delivery, and test for any delays that could impact user experience in time-sensitive applications, such as financial systems or IoT devices.\u00a0<\/li>
                                    2. Ensure that the system performs optimally even with network congestion or high event volume.\u00a0<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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                                      How can qAPI support your API testing requirements?\u00a0<\/strong><\/h3>

                                      qAPI offers end-to-end API testing services to support your growing API needs. Our cloud-based application is a fully managed service that makes it easy for developers\/testers\/QA teams to test, monitor and secure APIs of all types and sizes.\u00a0\u00a0<\/p>

                                      Here are some ways you can benefit from using qAPI.\u00a0<\/p>

                                      1. AI generated test cases for your APIs\u00a0<\/li>
                                      2. Automated workflows that are completely customizable.\u00a0<\/li>
                                      3. Performance and functional testing simulations with real-time visibility\u00a0<\/li>
                                      4. Run multiple iterations of same APIs to release new versions with ease.\u00a0<\/li><\/ol>

                                        Get started with qAPI by creating a free account today.<\/a>\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

                                        You\u2019re spending a lot of time testing APIs and under different conditions. With every test you run, the success rate you achieve, there are some learnings along the way that make you realize lot more than you usually account for.\u00a0 Consider a rapidly growing company working towards refining its digital infrastructure. Their engineering team must…<\/p>\n","protected":false},"author":4,"featured_media":3989,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"categories":[17,10],"tags":[],"class_list":["post-3965","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","category-resources"],"acf":[],"yoast_head":"\nWhat is the difference between SOAP vs REST vs GraphQL vs Streams? 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