About
NoSQL information is a productive method to store data that doesn’t guide to the necessities of a social SQL database. Figure out how to utilize the Azure gateway, the Azure Cosmos DB augmentation for Visual Studio Code, and the Azure Cosmos DB .NET Core SDK to work with your NoSQL information where you need, and give your clients high accessibility, regardless of where they are on the planet.
Create an Azure Cosmos DB database built to scale
Databases need to scale to meet both the information speed and volume requests made by worldwide crowds.
Assume you work for an online retailer and your database needs proportional to suit an extending item index. You likewise have a developing worldwide client base, and your clients anticipate that snappy reactions should their inquiries and quick updates to item accessibility.
Your database should scale consequently to represent new items, and it ought to have high throughput and low idleness to keep pace with your clients’ desires.
Choose the appropriate API for Azure Cosmos DB storage
You will compare the different APIs available in Azure Cosmos DB, highlighting and contrasting the different scenarios that would make them a good choice for a company.
At the end of this module, you will be able to:
- Explain the features of Core (SQL)
- Explain the features of MongoDB
- Explain the features of the Cassandra
- Explain the features of the Azure Table
- Explain the features of the Gremlin (graph)
- Choose the appropriate API for your Azure Cosmos DB account.
Insert and query data in your Azure Cosmos DB database
Envision you work for an internet dress retailer. You’ve been asked to model another information stockpiling answer for the stock framework dependent on Azure Cosmos DB. You’ve just settled on a test database construction and are currently investigating how to embed and question information with the SQL API, put away methodology, and client characterized capacities (UDFs).
Purplish blue Cosmos DB gives the Data Explorer device in the Azure entrance that you can use to play out every one of these tasks: including information, changing information, and making and running put away techniques. The Data Explorer can be utilized in the Azure entrance or it very well may be undocked and utilized in an independent program window, furnishing extra space to work with your information.
Store and access graph data in Azure Cosmos DB with the Graph API
Create an application that that uses an Azure Cosmos DB as a graph database. Store, retrieve and manipulate graph data and visualize it using Data Explorer.
In this module, you will:
- Determine if a graph database fits the data needs of your application
- Store data in a graph database from an application using the Gremlin API
- Query data in a graph database from an application using the Gremlin API
Store and Access NoSQL Data with Azure Cosmos DB and the Table API
Assume that you work for a camera organization. Your organization has built up a client confronting application that is at present utilizing tables in an Azure Storage record to store information about the focal points that the organization produces. Request from clients is developing quickly. You can without much of a stretch improve scaling, accessibility, and idleness by moving the application to Azure Cosmos DB. Engineers must have the option to list the points of interest, detriments, and use cases for the Table API in Azure Cosmos DB to approve their information stockpiling decisions to partners.
Right now, will gain proficiency with the procedure for making an Azure Cosmos DB database with the Table stockpiling API, and get familiar with the structure of the JSON reports utilized by the Table API.
Build a .NET Core app for Azure Cosmos DB in Visual Studio Code
In this module, you will:
- Create an Azure Cosmos DB account, database, and collection in Visual Studio Code using the Azure Cosmos DB extension
- Create an application to store and query data in Azure Cosmos DB
- Use the Terminal in Visual Studio Code to quickly create a console application
- Add Azure Cosmos DB functionality with the help of the Azure Cosmos DB extension for Visual Studio Code
Optimize the performance of Azure Cosmos DB by using partitioning and indexing strategies
In this module, you’ll use a console application to populate the database and simulate a set of queries. Then you’ll use Azure Cosmos DB monitoring tools to observe and understand the following key metrics of Azure Cosmos DB:
- Total requests made per second, and the proportion of requests rejected because the provisioned throughput is exceeded
- Total throughput, measured in Request Units per second (RU/s), and the distribution of throughput across partitions
- Total storage, measured in kilobytes (KB), and the distribution of data across partitions
After you understand these key metrics, we’ll assess different partitioning and indexing strategies to maximize the efficiency of your capacity.
Distribute your data globally with Azure Cosmos DB
Sending a parcel over the world under perfect system conditions takes several milliseconds. The best way to swindle the speed of light is to put information locally, with the goal that it has less separation to travel.
Envision you work at a web based dressing retailer, with enormous client populaces in Los Angeles, New York, and Tokyo. By recreating your information in various server farms far and wide, nearest to where your clients are, you guarantee they all have the quickest access to your items, so you don’t miss out to contenders.
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