What is OpenAPI and what are its top alternatives?
Top Alternatives to OpenAPI
t is a format that works with HTTP. A main goal of the specification is to optimize HTTP requests both in terms of the number of requests and the size of data packages exchanged between clients and servers. ...
It is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide. ...
GraphQL is a data query language and runtime designed and used at Facebook to request and deliver data to mobile and web apps since 2012. ...
It is an ISO/IEC approved, OASIS standard that defines a set of best practices for building and consuming RESTful APIs. It helps you focus on your business logic while building RESTful APIs without having to worry about the various approaches to define request and response headers, status codes, HTTP methods, URL conventions, media types, payload formats, query options, etc. ...
RESTful API Modeling Language (RAML) makes it easy to manage the whole API lifecycle from design to sharing. It's concise - you only write what you need to define - and reusable. It is machine readable API design that is actually human friendly. ...
gRPC is a modern open source high performance RPC framework that can run in any environment. It can efficiently connect services in and across data centers with pluggable support for load balancing, tracing, health checking... ...
An architectural style for developing web services. A distributed system framework that uses Web protocols and technologies. ...
- Amazon API Gateway
Amazon API Gateway handles all the tasks involved in accepting and processing up to hundreds of thousands of concurrent API calls, including traffic management, authorization and access control, monitoring, and API version management. ...
OpenAPI alternatives & related posts
related JsonAPI posts
- Easy to use486
- Great tool369
- Makes developing rest api's easy peasy274
- Easy setup, looks good155
- The best api workflow out there143
- History feature53
- It's the best53
- Adds real value to my workflow44
- Great interface that magically predicts your needs42
- The best in class app34
- Can save and share script11
- Fully featured without looking cluttered9
- Option to run scrips7
- Global/Environment Variables7
- Dead simple and useful. Excellent6
- Shareable Collections6
- Dark theme easy on the eyes6
- Awesome customer support5
- Great integration with newman5
- The test script is useful4
- Easy as pie3
- Saves responses3
- Makes testing API's as easy as 1,2,33
- This has simplified my testing significantly3
- I'd recommend it to everyone who works with apis2
- Mocking API calls with predefined response2
- Easy to setup, test and provides test storage1
- Postman Runner CI Integration1
- Now supports GraphQL1
- Continuous integration using newman1
- Pre-request Script and Test attributes are invaluable1
- <a href="http://fixbit.com/">useful tool</a>0
- Stores credentials in HTTP9
- Poor GraphQL support7
- Bloated features and UI7
- Cumbersome to switch authentication tokens7
- Not free after 5 users2
- Can't prompt for per-request variables2
- Support websocket1
- Import curl1
- Import swagger1
related Postman posts
We just launched the Segment Config API (try it out for yourself here) — a set of public REST APIs that enable you to manage your Segment configuration. A public API is only as good as its #documentation. For the API reference doc we are using Postman.
Postman is an “API development environment”. You download the desktop app, and build API requests by URL and payload. Over time you can build up a set of requests and organize them into a “Postman Collection”. You can generalize a collection with “collection variables”. This allows you to parameterize things like
workspace_name so a user can fill their own values in before making an API call. This makes it possible to use Postman for one-off API tasks instead of writing code.
Then you can add Markdown content to the entire collection, a folder of related methods, and/or every API method to explain how the APIs work. You can publish a collection and easily share it with a URL.
This turns Postman from a personal #API utility to full-blown public interactive API documentation. The result is a great looking web page with all the API calls, docs and sample requests and responses in one place. Check out the results here.
Postman’s powers don’t end here. You can automate Postman with “test scripts” and have it periodically run a collection scripts as “monitors”. We now have #QA around all the APIs in public docs to make sure they are always correct
Along the way we tried other techniques for documenting APIs like ReadMe.io or Swagger UI. These required a lot of effort to customize.
Writing and maintaining a Postman collection takes some work, but the resulting documentation site, interactivity and API testing tools are well worth it.
Our whole Node.js backend stack consists of the following tools:
- Lerna as a tool for multi package and multi repository management
- npm as package manager
- NestJS as Node.js framework
- TypeScript as programming language
- ExpressJS as web server
- Swagger UI for visualizing and interacting with the API’s resources
- Postman as a tool for API development
- TypeORM as object relational mapping layer
- JSON Web Token for access token management
The main reason we have chosen Node.js over PHP is related to the following artifacts:
- Flexibility: Node.js sets very few strict dependencies, rules and guidelines and thus grants a high degree of flexibility in application development. There are no strict conventions so that the appropriate architecture, design structures, modules and features can be freely selected for the development.
- Schemas defined by the requests made by the user73
- Will replace RESTful interfaces62
- The future of API's60
- The future of databases48
- Get many resources in a single request11
- Ask for what you need, get exactly that5
- Query Language4
- Evolve your API without versions3
- Fetch different resources in one request3
- Type system3
- Ease of client creation2
- Easy setup2
- Good for apps that query at build time. (SSR/Gatsby)1
- Backed by Facebook1
- Easy to learn1
- "Open" document1
- Better versioning1
- 1. Describe your data1
- Fast prototyping1
- Hard to migrate from GraphQL to another technology3
- More code to type.3
- All the pros sound like NFT pitches1
- Works just like any other API at runtime1
- Takes longer to build compared to schemaless.1
related GraphQL posts
I just finished the very first version of my new hobby project: #MovieGeeks. It is a minimalist online movie catalog for you to save the movies you want to see and for rating the movies you already saw. This is just the beginning as I am planning to add more features on the lines of sharing and discovery
For the #BackEnd I decided to use Node.js , GraphQL and MongoDB:
Node.js has a huge community so it will always be a safe choice in terms of libraries and finding solutions to problems you may have
GraphQL because I needed to improve my skills with it and because I was never comfortable with the usual REST approach. I believe GraphQL is a better option as it feels more natural to write apis, it improves the development velocity, by definition it fixes the over-fetching and under-fetching problem that is so common on REST apis, and on top of that, the community is getting bigger and bigger.
MongoDB was my choice for the database as I already have a lot of experience working on it and because, despite of some bad reputation it has acquired in the last months, I still believe it is a powerful database for at least a very long list of use cases such as the one I needed for my website
When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?
So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.
React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.
Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.
- Patterns for paging, sorting, filtering7
- ISO Standard5
- Query Language3
- No overfetching, no underfetching3
- Ask for what you need, get exactly that2
- Get many resources in a single request2
- Batch requests2
- Bulk requests ("array upsert")2
- Resource model defines conventional operations1
- Evolve your API by following the compatibility rules1
- Resource Modification Language1
- Overwhelming, no "baby steps" documentation1
related OData posts
- API Specification15
- Human Readable7
- API Documentation6
- Design Patterns & Code Reuse3
- API Modeling2
- Automatic Generation of Mule flow2
- Unit Testing2
- SDK Generation1
- API Mocking1
related RAML posts
- Higth performance20
- Easy setup11
- The future of API10
related gRPC posts
SignalR or gRPC are always sending and receiving data on the client-side (from browser to .exe and back to browser). And web application is used for graphical visualization of data to the user. There is no need for local .exe to send or interact with remote web API. Which architecture or framework do you suggest to use in this case?
By mid-2015, Uber’s rider growth coupled with its cadence of releasing new services, like Eats and Freight, was pressuring the infrastructure. To allow the decoupling of consumption from production, and to add an abstraction layer between users, developers, and infrastructure, Uber built Catalyst, a serverless internal service mesh.
Uber decided to build their own severless solution, rather that using something like AWS Lambda, speed for its global production environments as well as introspectability.
related REST posts
- AWS Integration36
- Less expensive1
- No websocket broadcast1