Top 20 Cosmos DB Interview Questions : most asked interview Question and answer for freshers

Top 20 Cosmos DB Interview Questions : Microsoft offers a globally distributed multi-model database solution called Azure Cosmos DB. With a single button click, it offers the flexibility to extend storage and throughput over an infinite number of Azure regions. Your preferred API, such as Gremlin, SQL, Cassandra, Tables, and MongoDB, can be used to manage and access the data.

A software engineer or developer with expertise in Microsoft Azure Cosmos DB database services is known as a Cosmos DB developer. They are in charge of planning, creating, and overseeing applications that make use of Cosmos DB’s storage, retrieval, and processing capabilities.

Here is The Top 20 Cosmos DB Interview Questions : most asked interview Question and answer for Freshers

1. How does Azure Cosmos DB provide predictable performance?

Azure Cosmos DB uses a variety of features and techniques to guarantee consistent performance.

Guaranteed Low Latency: Across all areas, Cosmos DB guarantees low latency for read and write operations. This implies that regardless of workload or location, your apps can always count on quick response times. Intelligent routing algorithms and a global network of data centers are used to accomplish this.

Automatic Scalability: Cosmos DB ensures that you always have the appropriate amount of capacity to manage your workload by automatically scaling up or down based on the requirements of your application. This helps to maintain constant performance by doing away with the requirement for manual provisioning and management.

Consistent Throughput: Consistent throughput guarantees from Cosmos DB ensure that your applications may continue to operate at a predictable level even during periods of high demand. To do this, each container is allocated a certain amount of throughput capacity, which is subsequently dispersed over the underlying infrastructure.

Optimized Indexing: For your data, Cosmos DB automatically builds and maintains indexes so that queries can run quickly. This lowers latency and enhances query performance.

Also read this – Top Redis Interview Questions: Prepare for Your Job Interview most asked Questions for freshers

2.Can I use multiple APIs to access the data in Cosmos DB?

Yes, you can access data in Cosmos DB using a variety of APIs. One of the main benefits of the database is its adaptability. The principal available APIs are as follows:

• SQL API
• MongoDB API
• Gremlin API
• Table API
• Cassandra API
• Azure Functions API

3.How does Cosmos DB cost is calculated?

Provisioned throughput and storage are the two main parameters used to determine Cosmos DB cost. The capacity you allot to your database or container is known as provisioned throughput, and it is expressed in Request Units per second (RU/s). The number of reads, writes, and queries your database can process in a second is measured as RU/s. Whether or whether you use all of the provided throughput, you are still charged for it.

The quantity of data that is kept in your Cosmos DB account determines how much storage will cost. Every gigabyte of storage utilized is subject to a set fee. The overall amount of data stored, including backups and indexes, determines the storage cost. There’s also a minimum billable storage quantity, which implies that even if you utilize less storage, you will still be paid for it.

Also read this – Crack Your Xamarin Interview with These Questions most asked Interview Questions for freshers

4.Explain the throughput.

In the context of Cosmos DB, throughput is your database’s or container’s capacity or performance. Request Units per Second (RU/s) are used to measure it. In essence, RU/s is a measure of how many read, write, and query operations your database can process in a second.

The performance of your database or container is directly impacted by the number of RU/s you provision for it. Your database can handle more operations at once if you provision a greater RU/s, which will improve overall performance and response times. Provisioning more RUs than necessary, however, may result in extra expenses. To choose the best RU or RUs for your database, it’s critical to thoroughly evaluate the workload and needs of your application.

Also read this – Top 20 most asked Ruby Interview Questions for freshers

5.Does Azure Cosmos DB provide free account?

Yes, there is a free tier available for Azure Cosmos DB that gives a restricted set of resources at no expense. For testing and playing with Cosmos DB without having to pay a lot of money, this free tier is perfect.

Within Cosmos DB, databases and containers can be created and managed using a specific amount of provided throughput (RU/s) and storage included in the free tier. It’s crucial to remember that there are restrictions on the maximum number of databases, containers, and data sizes that may be used with the free tier. You will be charged for more resources after you go over these caps.

You can quickly move to a subscription tier that provides more features and resources if the requirements of your application demand more than what the free tier can provide. Cosmos DB offers a range of pricing options to suit different budgets and workloads.

6.What are the different data models supported by Azure Cosmos DB?

• Document: In Cosmos DB, this is the most often utilized data model. Semi-structured and unstructured data can be easily stored and queried thanks to its use of the schema-free JSON format. The SQL, MongoDB, and Cassandra APIs support this data model.
• Key-Value: The foundation of this data format is a key-value store, in which every item is saved as a value and given a unique key for identification. It is compatible with the Table API.
• Graph:  This data model is used to store and query graph data, such as social networks, recommendation systems, and hierarchical data. It is supported by the Gremlin API.
• Column-family: Wide-column data, such time series and Internet of Things data, can be stored and queried using this data type. The Cassandra API supports it.

7.How does Azure Cosmos DB handle data indexing and querying?

By default, Azure Cosmos DB automatically indexes each and every property in your data. As a result, index definition and management are no longer necessary, which streamlines development and enhances query performance. Cosmos DB uses these indexes to quickly find and get pertinent data when you query your database.

Even if automated indexing is practical, there are situations where you might need to modify the indexing policy. To maximize performance and save storage expenses, you can eliminate pointless characteristics from indexing, for instance, if your large dataset has numerous properties and you only use a portion of them for querying. To further improve query efficiency, composite indexes can be made for queries involving many attributes.

8.Can you explain the concept of partitioning in Azure Cosmos DB?

With Azure Cosmos DB, partitioning is a technique that divides your data into several physical partitions, enabling horizontal database scaling. Performance is enhanced by this, particularly when handling big datasets or heavy traffic.

The partition key is the central idea of partitioning. This is a feature of your data that helps you put related items in logical groups. A logical partition contains all items that have the same partition key value. To guarantee even data distribution and load balancing, Cosmos DB then automatically divides these logical partitions among physical partitions.

You may maximize the scalability and performance of your queries by selecting your partition key carefully. Ensuring that your data is spread uniformly and that queries are efficiently directed to the appropriate partitions may be achieved with a well selected partition key.

9.How does Azure Cosmos DB handle data consistency and availability?

To accommodate varying application needs, Azure Cosmos DB provides strong consistency, eventual consistency, and session consistency levels. All reads guarantee that the most recent writes to the database are returned, thanks to strong consistency. Applications that demand precise data consistency, such real-time collaboration or financial transactions, are best suited for this.

All writes will eventually spread to every database replica, according to eventual consistency. Applications that can handle a little latency in data updates should use this. Session consistency ensures that reads within a session see the most recent writing done by that session, which strikes a balance between eventual and strong consistency. Applications that need consistency inside a particular context or user interaction may find this helpful.

Cosmos DB offers high availability via automated replication and failover in addition to consistency. Your data is globally dispersed and resilient to failures since the database is duplicated over several locations. Cosmos DB can automatically failover to a healthy region in the event of a region failure, reducing downtime and guaranteeing data availability.

10.How does Azure Cosmos DB handle and manage data backups?

Data durability and catastrophe recovery are guaranteed by the automatic data backups handled by Azure Cosmos DB. Multiple locations have duplicate copies of the database, and regular backups are made to ensure your data is always up to date. Because of the geo-redundant storage of these backups, data loss from hardware malfunctions, natural disasters, or inadvertent deletions is prevented.

The ability to make manual backups at predetermined intervals is another feature provided by Cosmos DB. Data preservation at crucial times, as before a significant deployment or update, may benefit from this. If needed, you can then restore your database to a prior version. Furthermore, Cosmos DB has point-in-time restore capability, which lets you retrieve data to a specified moment in the last three or 24 hours, based on the consistency level you’ve set.

11.How can you integrate Azure Cosmos DB with other Azure services?

Azure Cosmos DB easily connects to a wide range of other Azure services to build robust and all-inclusive solutions. For example, it may be used in conjunction with Azure Functions to create serverless apps that launch events in response to modifications in Cosmos DB data. Event-driven architectures and real-time processing are made possible by this.

Workflows utilizing Cosmos DB can also be orchestrated using Azure Logic Apps. You can design automated procedures that, when certain circumstances are met in your database, cause actions to be taken, such interacting with other systems or sending notifications. This increases productivity and streamlines intricate corporate procedures.

12.What are Request Units in Cosmos DB?

Request Units (RUs) In Azure Cosmos DB, Request Units (RUs) represent your database or container’s capacity or performance. They show how much work, including reads, writes, and queries, your database can process in a second.

The throughput and performance of your database or container are dependent on the amount of RUs you offer. Your database can manage more processes at once with a greater RU provision, which leads to quicker reaction times and improved performance all around. Provisioning more RUs than necessary, however, may result in extra expenses. Finding the ideal RU supply for your database requires carefully evaluating the workload and needs of your application.

13.Describe the Purchasing Models Available in Azure SQL Database.

vCore Purchasing Model: Users can select the physical attributes of hardware according to the requirements of their applications using the vCore purchase mechanism. Customers in this model have the autonomy to decide how much storage, processing power, etc. to scale.

DTU-based Purchasing Model: Customers can choose between multiple service tiers based on fixed compute size, storage, read-write speeds, and backup retention time using a purchase model based on Database Transaction Units (DTUs).

14.What are the Different Deployment Models Provided by Azure SQL Database?

Single Database: A database with a dedicated database engine, its own set of resources, performance monitoring, and service tiers is created using a single database type deployment methodology.

Elastic Pool:The deployment concept of elasticity pools allows consumers to buy resources for a pool that is shared by several databases. Depending on how the resources are used, we can add or remove databases from the pool. The issue of resource overprovisioning and underprovisioning is resolved by an elastic pool.

15.Why do you think it’s a good idea to use Cosmos DB as the backend for your application?

I believe Cosmos DB would be a suitable choice for my application’s backend for a number of reasons. Firstly, my application will be able to scale to consumers worldwide because Cosmos DB is a globally distributed database. Secondly, Cosmos DB provides a variety of consistency levels, allowing me to select the one that best suits my application. Lastly, Cosmos DB provides a range of APIs, allowing me to select the one most appropriate for my use case.

16. Can you explain what Azure Table Storage is and how does it relate to Cosmos DB?

Azure Table Storage is a cloud-based NoSQL data storage solution made to support applications that need a lot of data by offering highly scalable, dependable, and reasonably priced storage. Built on top of Azure Table Storage, Cosmos DB is a cloud-based NoSQL database service. It provides further functionalities and features including data indexing, transaction processing, and horizontal scalability that aren’t found in Azure Table Storage.

17.What are some ways to make Cosmos DB more cost-effective?

Using the Azure Cosmos DB free tier is one option to reduce the cost of Cosmos DB. A shared throughput of 400 RU/s and 5 GB of storage are available in the free tier. You can also take use of the reserved capacity of the Azure Cosmos DB to save even more money. When you commit to a specific quantity of throughput and storage for a set amount of time, the reserved capacity offers a significant reduction (up to 70%) on the cost of Cosmos DB.

18.How is data stored in Cosmos DB?

The distributed database architecture used by Azure Cosmos DB is built for high availability, scalability, and performance. To achieve even distribution of data and load balancing, data is stored in logical partitions and subsequently spread across several physical partitions.

Data is stored in the database using a document model, which arranges the data into hierarchical structures made up of key-value pairs. Cosmos DB’s versatile nature makes it possible to store both organized and unstructured data, which makes it appropriate for a variety of uses. Additionally, all attributes in the database can be automatically indexed, which improves query performance and does away with the need for manual index administration.

19. Can you explain what indexing policies are in the context of Cosmos DB?

Azure indexing policies The indexing of data inside a container is determined by Cosmos DB. Every property of every item is automatically indexed by Cosmos DB by default, generating range indexes for both string and integer data types. As a result, effective querying is possible without the need for explicit index management.

20.Can you run bulk updates on Cosmos DB data?

It is possible to update Cosmos DB data in bulk. When you need to efficiently update a lot of papers, this is quite helpful. Cosmos DB offers multiple techniques for large-scale updates.