20 Distributed Database Interview Questions and Answers

A distributed database is a database that is spread across multiple locations, often across different computers. In a distributed database interview, you may be asked questions about how you would manage and query a database that is spread out in this way. Answering these questions confidently can help you secure the position you’re interviewing for. In this article, we’ll review some of the most common distributed database questions and provide guidance on how to answer them.

Distributed Database Interview Questions and Answers

Here are 20 commonly asked Distributed Database interview questions and answers to prepare you for your interview:

1. What is a distributed database?

A distributed database is a database that is spread out across multiple locations, often on different servers. This can be done for a variety of reasons, such as to improve performance or to increase availability.

2. Can you explain what data distribution is in the context of databases?

In a distributed database, data is physically stored across multiple computers that are connected together in a network. This allows for greater scalability and availability than a traditional, single-computer database.

3. How do you define a distributed system?

A distributed system is a system where components are spread out across a network and interact with each other to achieve a common goal.

4. What are some features oif a distributed database?

A distributed database is a database that is spread out across multiple locations. This can be done for a variety of reasons, such as to improve performance or to increase availability. Some features of a distributed database include the ability to replicate data across multiple locations, the ability to partition data across multiple locations, and the ability to manage data across multiple locations.

5. What are the main advantages and disadvantages of using a distributed database?

The main advantage of using a distributed database is that it can provide better performance and availability than a traditional centralized database. The main disadvantage is that it can be more complex to manage and maintain.

6. Are there different types of distributed databases? If yes, then which ones have you worked with?

Yes, there are different types of distributed databases. I have worked with two main types: shared-nothing and shared-disk. In a shared-nothing distributed database, each node has its own private storage and there is no central storage that is shared by all nodes. This type of database is typically more scalable and can handle more concurrent users than a shared-disk database. In a shared-disk database, all nodes have access to a common storage area, such as a SAN or NAS. This type of database is typically easier to manage than a shared-nothing database, but is not as scalable.

7. What are the basic requirements for creating a distributed database?

In order to create a distributed database, you will need to have a database management system that supports distributed databases, as well as multiple computers that are connected to each other. The computers will need to be able to share data and access the same database management system.

8. What is the difference between centralized databases and distributed databases?

A centralized database is one in which all data is stored in a single location. A distributed database is one in which data is stored across multiple locations, often on different servers. The main advantage of a distributed database is that it can be more scalable than a centralized database, as it can more easily accommodate growth.

9. Is it possible to replicate data from one node to another? If yes, how would you go about doing that?

Yes, it is possible to replicate data from one node to another. There are a few different ways to do this, but one common method is to use a tool like rsync. Rsync is a tool that can be used to synchronize files and directories between two different locations. In this case, you would use it to replicate the data from one node to another.

10. What’s your understanding of consistency in the context of distributed databases?

Consistency in a distributed database means that all nodes in the system contain the same data. This is usually achieved through replication, where each node contains a copy of the data.

11. What is the best way to ensure fault tolerance in a distributed database?

There are a few different ways to ensure fault tolerance in a distributed database, but the most common method is to use replication. This involves having multiple copies of the same data stored in different locations. If one copy of the data is lost or corrupted, then the other copies can be used to restore the data.

12. Does sharding make sense when designing a distributed database?

Sharding can be a helpful way to improve performance in a distributed database by distributing data across multiple servers. However, it is important to consider whether sharding makes sense for your particular application before implementing it, as it can complicate your database design and add overhead.

13. What is horizontal scaling? Why is it important in the context of distributed databases?

Horizontal scaling is the process of adding more nodes to a system in order to increase its capacity or performance. In the context of distributed databases, horizontal scaling is important because it allows the database to continue to function even if one or more of its nodes fail. By adding more nodes, the database can continue to operate as long as there are still nodes remaining.

14. What do you understand about indexing on a distributed database?

Indexing on a distributed database is a process of creating and storing a data structure that can be used to quickly locate specific records within the database. This data structure is typically a tree or a hash table, and it can be used to speed up the process of searching for records by allowing the database to quickly narrow down the search space.

15. What is a load balancer? What is its role in a distributed database?

A load balancer is a device that helps to distribute traffic evenly across a network of servers. In a distributed database, the load balancer helps to ensure that each server in the network is able to handle its share of traffic and requests. This helps to prevent any one server from becoming overloaded and ensures that the database as a whole is able to function properly.

16. How can you implement ACID compliance in a distributed database?

In order to implement ACID compliance in a distributed database, you need to use a two-phase commit protocol. This ensures that all of the nodes in the distributed database are in sync and that any changes that are made to the database are made in a consistent manner.

17. What are some common use cases for distributed databases?

There are many potential use cases for distributed databases. Some common examples include organizations with multiple locations that need to share data, companies that need to share data with partners or suppliers, or any situation where data needs to be shared across a wide area network.

18. What are the major differences between a cloud-based database and an on-premise distributed database?

The biggest difference between a cloud-based database and an on-premise distributed database is that the former is hosted on a remote server, while the latter is hosted on a local server. This means that a cloud-based database is more scalable and can be accessed from anywhere, while an on-premise distributed database may be more expensive to set up and maintain.

19. What is a NoSQL database? Do they fall under the umbrella of distributed databases?

NoSQL databases are a type of database that does not use the traditional relational model. Instead, they use a more flexible schema-less model. This makes them well-suited for handling large amounts of data that may be constantly changing. While NoSQL databases can be distributed, not all of them are.

20. What is scale out in the context of distributed databases?

Scale out is the process of adding more nodes to a distributed database in order to increase capacity or performance. This can be done by adding more servers, storage devices, or other components to the system.