与iOS云存储选项 [英] Cloud storage options with iOS
问题描述
我试图建立一个后端，我可以有很多用户相互之间的iPhone应用程序我创建沟通。我试着与核心数据，谷歌应用程序引擎，谷歌云存储和Amazon Web Services的工作（RDS和放大器;弹性魔豆）。不幸的是，周试图得到任何这方面的工作后，这一切都不！
I'm trying to create a back-end in which I can have many users communicate with each other amongst an iPhone app I'm creating. I've tried working with Core Data, Google App Engine, Google Cloud Storage, and Amazon Web Services (RDS & Elastic Beanstalk). Unfortunately, after weeks of trying to get any of this working, none of it will!
我一直在试图取得联系的人谁知道如何创业公司（当他们的小）一样的Instagram，Path和Pinterest的已成功地做到这一点。但是，每个人都在那里似乎鄙视这个东西，就像我正在成长为...
I've been trying to get in touch with someone who would know how startups (when they were little) like Instagram, Path, and Pinterest have managed to do this. But everyone out there seems to despise this stuff as much as I'm growing to...
我会有人简单地绘制出到底我需要创建一个后台数据库，我可以查询数据保存，并和许多用户可以看到爱。这意味着，仅仅SQLite的，核心数据，或者自行解析是不会在这里工作！
I would love for someone to simply map out EXACTLY how I need to create a back-end database that I can save and query data to and from that many users can see. That means that just SQLite, Core Data, or Parse by itself isn't going to work here!
某种形式的教程将是令人难以置信的。
A tutorial of some kind would be incredible.
推荐答案
首先，技术如的coredata和SQLite是典型的本地设备存储空间。本地设备的存储是不会让你共享的云存储。
First off, technologies like CoreData and sqlite are typically local device storage. Local device storage is not going to get you shared cloud storage.
Parse.com是一种快速的方式为设备访问云存储和走了快。尤其适用于游戏和其他移动应用程序通过一个应用程序ID和应用程序键进入云数据。这是简单的存储，以避免创建自己的后台，如果它填补你所有的需求和要求。
Parse.com is a fast way for devices to access cloud storage and get going fast. Especially useful for games and other mobile apps to access cloud data via an app id and app key. It's simple storage to avoid creating your own backend if it fills all your needs and requirements.
当你去了，你滚你自己的服务和多设备访问，你需要寻找到暴露你的Web API的云应用程序的多租户云后端。暴露的RESTful API通过HTTP是伟大的设备和Web客户端。暴露的数据作为JSON特别conventient为Web和容易消耗的设备。
When you get to a multi-tenant cloud backend where you roll your own services and multiple devices accessing your cloud application you need to look into exposing your web API. Exposing RESTful API over http is great for devices and web clients. Exposing the data as JSON is especially conventient for the web and easily consumed by devices.
在云中访问这些Web服务端点某种后端存储的是通过复式客户并发访问进行了优化。这是一个典型的SQL后端如MySQL，SQLServer的等等或的NoSQL解决方案像的mongodb ， CouchDB的，等...
Those web service end points in the cloud access some sort of backend storage which is optimized for concurrent access by mutliple clients. This is typically a SQL backend like MySQL, SQLServer etc... or a NoSQL solution like mongodb, couchDB, etc...
一些前端的Web API技术寻找到：
Some front end web api technologies to look into:
- ASP.net 网络API
- Ruby on Rails的
- Node.js的
- 等等...
- ASP.net web api
- Ruby on Rails
- Node.js
- etc...
一些后端存储技术寻找到：
Some back end storage technologies to look into:
- SQL： MySQL的，的SQLServer/Azure SQL ，甲骨文
- 的NoSQL：MongoDB中，CouchDB的，亚马逊S3简单的存储，等等...
- SQL: MySQL, SQLServer/Azure SQL, Oracle
- NoSQL: MongoDb, CouchDb, Amazon S3 simple storage, etc...
如果数据是由许多许多多租户客户端，后端可以按比例放大（越来越大），或得到分片。分片是其中多个用户的数据被分成多个数据库或数据存储带有某种查找算法的请求找到该用户的数据被存储。前端的Web服务器API抽象的后端存储。
If the data is used by many many multi-tenant clients, the backends can scaled up (larger and larger) or get sharded. Sharding is where the data for multiple users is split into many databases or datastores with some sort of lookup algorithm for requests to find where that users data is stored. The front end web api servers abstract the backend storage.
最后，你最终会需要某种形式的缓存/快速查找技术（如果你成功了：）：
Finally, you'll end up needing some sort of caching/fast lookup technology (if you're successful :):
- Redis的：快过插槽记忆存储
- memcached的：Facebook的用途 - 在多个前端服务器在内存中缓存简单的按键值
- Redis: fast in memory storage over sockets
- memcached: facebook uses - simple key value in memory caching across many front end servers.
您的问题是一个开放结束了广泛的问题，因此受到许多谷歌上搜索这些术语和技术的开始。
Your question is an open ended up broad question so start by googling many of these terms and technologies.
每个这些链接将有资源和教程。获取云虚拟机，发挥每个并决定哪些最适合您的需要。没有一个放之四海而皆准的解决方案。
Each of these links will have resources and tutorials. Get a cloud VM, play with each and decide which fits your needs best. There is no one size fits all solution.
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