AzureCloud-FINAL-kb

>> Hello, everyone. Over the next few minutes, I'll talk about some of the features that make Azure Cosmos DB, a good choice for globally distributed data storage. If you're new to Cosmos DB, you might be wondering why you should choose it for your application, or perhaps even why your organization or data architect has chosen to use Cosmos DB over other data storage options when there are so many to choose from. First of all, [WHAT EXACTLY IS A GLOBALLY DISTRIBUTED DATABASE?] what exactly is a globally distributed database? Well, in a nutshell, globally distributed databases enable your data to live in virtually every region of the world where it's needed. Now that's important for two reasons. First, if there's an outage in one region, you have copies of your data sitting around the world that your application can fail over to. Second, your applications can pull data from the region closest to your users to reduce data access latency. The question then is if your data is distributed and you make changes to data in one region, how do you sync these changes to all other instances of your data located in other regions across the globe? Well, answering that question turns out to be a key reason to choose Cosmos DB. It gives you more control over consistency than any other distributed database offering today. When you're dealing with distributed data, you need to think about how you want your data to sync between locations, given the tradeoffs between the availability and staleness of the data. [AVAILABILITY AND STALENESS] [LATENCY] The latency you're willing to accept during queries. And the cost of throughput [COST] to get the data to its destinations. This is something you need to consider upfront as you begin to architect your application. Now historically, distributed database services have not been very flexible, there was either no choice at all, or you had to choose between the two extreme ends of the continuum of consistency. It's basically the difference between choosing whether everything is always in sync regardless of the cost versus everything potentially being out of sync and never really being sure you're working with the latest data. Again, these are two extremes along the continuum of consistency, and thankfully Cosmos DB gives us more choices. Azure Cosmos DB offers five consistency models that tradeoff to varying degrees between availability, latency, and throughput. You select the level that offers the right balance for your scenario. Since no one size will fit all in terms of consistency model, this makes Cosmos DB a great choice for distributed data. We talk about the attributes of these consistency models at length in our Architect Modules on Cosmos DB later. So the main takeaway for now as you are getting started is that depending on your organization's needs, you can spend less to keep your data in sync by allowing it to sync up eventually or spend more to increase the throughput of the data and keep it fully in sync at all times. The second reason you might choose Cosmos DB is that it is fully schema-agnostic. [SCHEMA AGNOSTIC] This means that, as a developer, you can iterate the schema of your application without worrying about database schema and/or index management. It enables you to use key-value, graph, and document data together in a single service. In addition, Cosmos DB automatically indexes [AUTOMATIC INDEXING] all the data it ingests without requiring any schema or indexes. And serves up blazing fast reads and writes that are backed by a Service Level Agreement. And finally, the third reason you might choose Cosmos DB is that it supports different APIs for accessing the data. [MANY APIS SAME DATA STORE] In other words, if you come from a SQL server background, you can think of the organization of your data in a relational way, and query it using a familiar SQL-like syntax. On the other hand, if you're coming from a MongoDb background, there's an API that you'll feel right at home using. It's the same data in storage, but the way you access it and think about it can be dramatically different. Cosmos DB currently supports five different APIs. [SQL, MONGO DB] In addition to SQL and Mongo DB, [CASSANDRA API] there's a Cassandra API, [GREMLIN API] a Gremlin API, [TABLE API] and a Table API for those who want to move on from Azure Table Storage. So to recap, Azure Cosmos DB is a globally distributed data store, it gives you five consistency models supported by the Cosmos DB replication protocol that provide a clear tradeoff between specific consistency guarantees and performance, and therefore, cost. It also supports multiple data models and popular APIs for accessing and querying data. And finally, it's schema-less, yet indexes everything automatically for extremely fast data retrieval with money-back performance guarantees. I hope you found this overview helpful. Thanks for watching.