1. What is the difference between SQL and NoSQL databases?
Answer: SQL databases, also known as relational databases, store data in a structured, tabular format and use SQL (Structured Query Language) to access and manipulate the data. NoSQL databases, on the other hand, store data in a variety of formats, including key-value pairs, documents, and graph structures, and do not use SQL to access the data. NoSQL databases are often favored for their flexibility and scalability, as well as their ability to handle large amounts of unstructured data.
2. Can you explain what Cosmos DB is and why it is important?
Answer: Cosmos DB is a globally distributed, multi-model database service provided by Microsoft Azure. It supports a variety of data models, including document, key-value, graph, and columnar, and offers a range of consistency levels to meet the needs of different applications. Cosmos DB is important because it provides a highly scalable, globally distributed database solution that can be used to build and deploy applications in the cloud. With its strong consistency guarantees and low latency, Cosmos DB is ideal for building fast, reliable, and globally distributed applications.
3. What is the difference between a relational database and a non-relational database?
Answer: A relational database is a type of database that stores data in a structured, tabular format and uses SQL to access and manipulate the data. A non-relational database, on the other hand, does not use a structured, tabular format to store data and does not use SQL to access the data. Instead, non-relational databases store data in a variety of formats, including key-value pairs, documents, and graph structures.
4. Can you explain the architectural differences between relational and non-relational databases?
Answer: Relational databases typically follow a client-server architecture, with a central database server that manages all data access and manipulation. Non-relational databases, on the other hand, often use a more distributed architecture, with multiple nodes that can be used to store and process data. This allows non-relational databases to scale more easily as the amount of data grows, and provides increased fault tolerance in the event of a failure. Additionally, non-relational databases often use more relaxed consistency models, such as eventual consistency, which allows them to provide low-latency data access even in large-scale, globally distributed deployments.
5. What is data partitioning and why is it important?
Answer: Data partitioning is the process of dividing a large database into smaller, more manageable chunks called partitions. This is done to improve the performance, scalability, and availability of the database. By dividing the data into partitions, each partition can be stored and processed separately, reducing the load on any single server and allowing the database to scale more easily as the amount of data grows.
6. Can you explain what Cosmos DB is and why it is important?
Answer: Cosmos DB is a globally distributed, multi-model database service provided by Microsoft Azure. It supports a variety of data models, including document, key-value, graph, and columnar, and offers a range of consistency levels to meet the needs of different applications. Cosmos DB is important because it provides a highly scalable, globally distributed database solution that can be used to build and deploy applications in the cloud. With its strong consistency guarantees and low latency, Cosmos DB is ideal for building fast, reliable, and globally distributed applications.