FaunaDB Interview Questions and Answers for 2 years experience

0
100 FaunaDB Interview Questions & Answers (2 Years Experience)

  1. What is FaunaDB?

    • Answer: FaunaDB is a serverless, distributed NoSQL database built for modern applications. It offers a powerful query language (FQL) and integrates seamlessly with various programming languages and frameworks. Its key features include ACID transactions, built-in security, and automatic scaling.

  2. Explain the difference between FaunaDB and traditional relational databases.

    • Answer: FaunaDB is a NoSQL database, while traditional relational databases (like MySQL, PostgreSQL) are SQL databases. Key differences include data modeling (document vs. relational), query language (FQL vs. SQL), and scalability approaches (serverless vs. more manual scaling). FaunaDB excels in scenarios requiring flexible schemas and high scalability, while relational databases are better suited for structured data and complex joins.

  3. What is FQL (Fauna Query Language)? Give an example.

    • Answer: FQL is FaunaDB's query language. It's a declarative language that allows you to interact with the database. Example: `Select(Get(Ref(Classes, "myClass"), {"data": {"key": "value"}}))` This retrieves a document from the "myClass" collection with specific data.

  4. Describe FaunaDB's data modeling approach.

    • Answer: FaunaDB uses a document-based model. Data is organized into collections (similar to tables in relational databases) and each document within a collection is a JSON-like object. This flexible schema allows for easy adaptation to evolving data structures.

  5. How does FaunaDB handle ACID transactions?

    • Answer: FaunaDB guarantees ACID properties (Atomicity, Consistency, Isolation, Durability) across all database operations. This ensures data integrity even in concurrent scenarios.

  6. Explain the concept of Collections and Indexes in FaunaDB.

    • Answer: Collections hold documents. Indexes are created on collections to optimize query performance. They allow efficient retrieval of documents based on specific fields.

  7. What are UDFs (User Defined Functions) in FaunaDB? Provide a simple example.

    • Answer: UDFs are custom functions written in FQL that you can use to encapsulate logic and reuse it across your application. Example: `Query(Lambda(doc, Let( { name: doc.data.name }, { name: name, upperName: ToUpper(name) } )))`

  8. How does FaunaDB handle security?

    • Answer: FaunaDB uses a role-based access control (RBAC) system. You define roles with specific permissions, and users are assigned to those roles, limiting their access to data and operations.

  9. Explain the concept of roles and permissions in FaunaDB.

    • Answer: Roles define a set of permissions. Permissions grant access to specific collections, indexes, or functions. Users are assigned roles, inheriting the associated permissions.

  10. How do you handle pagination in FaunaDB queries?

    • Answer: Pagination is handled using the `Map` function in conjunction with `limit` and `after`. You specify the number of documents per page (`limit`), and use the last document's reference from the previous page (`after`) to fetch the next page.

  11. Describe your experience working with FaunaDB's client libraries (e.g., Node.js, Python).

    • Answer: [Describe your experience, including specific libraries used, challenges faced, and solutions implemented. Be detailed and specific. Example: "I've extensively used the FaunaDB Node.js driver to build a microservice. I encountered challenges with handling asynchronous operations and optimized the code for better performance using promises and async/await."]

  12. How would you optimize a slow FaunaDB query?

    • Answer: [Describe strategies, mentioning appropriate indexes, efficient querying techniques, and query profiling tools. Example: "First, I would analyze the query using FaunaDB's profiling tools. If slow, I would check for missing indexes, optimize the FQL to reduce computation, and consider denormalization if the data access pattern justifies it."]

  13. Explain how you would design a FaunaDB schema for a specific application (e.g., e-commerce, blogging platform).

    • Answer: [Describe your design, including collections, indexes, and relationships. For example, for an e-commerce platform, you would discuss collections for products, users, orders, and relevant indexes for optimizing searches and data retrieval. Be precise and show understanding of schema design principles.]

  14. How would you handle data migrations in FaunaDB?

    • Answer: [Explain your approach, emphasizing the use of UDFs or external scripts for transforming data, and strategies for handling data consistency. Mention version control and rollback mechanisms.]

  15. What are some common challenges you faced while working with FaunaDB, and how did you overcome them?

    • Answer: [Describe your experiences with challenges such as query optimization, schema design, error handling, or specific library issues. Highlight your problem-solving skills and ability to find solutions.]

  16. Explain your understanding of FaunaDB's pricing model.

    • Answer: [Describe FaunaDB's pay-as-you-go model, including factors like database operations, storage, and bandwidth usage.]

  17. What are some alternatives to FaunaDB? When would you choose FaunaDB over those alternatives?

    • Answer: [Mention alternatives like MongoDB, Cosmos DB, and Firebase. Explain when FaunaDB's strengths (ACID transactions, serverless nature, FQL) make it a preferable choice.]

Thank you for reading our blog post on 'FaunaDB Interview Questions and Answers for 2 years experience'.We hope you found it informative and useful.Stay tuned for more insightful content!