Fundamentals

1. What is MongoDB?

   • MongoDB is a popular NoSQL document-oriented database that stores data in flexible, JSON-like documents.

2. What are the key features of MongoDB?

   • Document-oriented: Stores data in flexible, JSON-like documents.
   • Schema-less: No strict schema definition, allowing for flexible data modeling.
   • Scalability: Easily scales horizontally by adding more servers.
   • High Availability: Provides high availability through replication and sharding.
   • Indexing: Supports various indexing options for efficient data retrieval.

3. What is a document in MongoDB?

   • A flexible, JSON-like structure that can contain key-value pairs of various data types.

4. What are collections in MongoDB?

   • Groups of documents within a database.

5. What are databases in MongoDB?

   • Top-level containers that hold collections.

Data Modeling

6. How do you design a schema in MongoDB?

   • Consider data relationships, query patterns, and future scalability needs.
   • Use embedded documents or references to model relationships.

7. What are the advantages of using embedded documents?

   • Improved query performance, reduced data fragmentation.

8. What are the advantages of using references (foreign keys)?

   • Reduced data duplication, improved data consistency.

9. How do you handle one-to-many relationships in MongoDB?

   • Use embedded documents or references (often with an array of IDs).

10. How do you handle many-to-many relationships in MongoDB?

• Use a separate collection to store the relationships between documents.

Data Types

11. What are the common data types supported by MongoDB?

• String, integer, boolean, array, object, date, etc.

12. What is the BSON format?

• Binary JSON, the format used by MongoDB to store data internally.

Queries

13. How do you perform basic find queries in MongoDB?

• Use the find() method with optional query filters.

14. What are projection operators in MongoDB?

• Specify which fields to include or exclude from the query results.

15. How do you sort query results in MongoDB?

• Use the sort() method.

16. How do you limit the number of results in a query?

• Use the limit() method.

17. How do you skip the first N results in a query?

• Use the skip() method.

18. What are compound indexes in MongoDB?

• Indexes created on multiple fields to improve query performance for specific query patterns.

19. Explain the concept of text indexing in MongoDB.

• Creates an index for full-text search capabilities.

20. How do you perform update operations in MongoDB?

• Use the updateOne(), updateMany() methods.

21. How do you perform delete operations in MongoDB?

• Use the deleteOne(), deleteMany() methods.

Aggregation Framework

22. What is the aggregation framework in MongoDB?

• A powerful tool for data processing and transformation.

23. What are some common aggregation pipeline stages?

• $match, $project, $group, $sort, $limit, $lookup.

24. How do you perform a group by operation in MongoDB?

• Use the $group stage.

25. How do you perform a join operation in MongoDB?

• Use the $lookup stage.

Indexing

26. What is an index in MongoDB?

• A special data structure that improves query performance.

27. What are the different types of indexes in MongoDB?

• Single field indexes, compound indexes, text indexes, geospatial indexes.

28. When should you create an index?

• When frequently querying on a specific field or combination of fields.

29. What are the drawbacks of excessive indexing?

• Increased write operations and storage overhead.

Replication

30. What is replication in MongoDB?

• Creating multiple copies of a dataset across different servers for high availability and fault tolerance.

31. What are the roles in a replica set?

• Primary, secondary, and arbiters.

32. How does data replication happen in MongoDB?

• Oplog (operation log) is used to replicate data changes between members of a replica set.

Sharding

33. What is sharding in MongoDB?

• Distributing data across multiple servers to improve scalability and performance.

34. How does sharding work in MongoDB?

• Data is partitioned across shards based on a sharding key.

35. What is a shard key?

• A field or combination of fields used to determine which shard a document belongs to.

Administration

36. How do you monitor MongoDB performance?

• Use the db.serverStatus() command, monitoring tools, and performance counters.

37. How do you back up a MongoDB database?

• Use mongodump or mongorestore, or utilize cloud-based backup services.

38. How do you restore a MongoDB database from a backup?

• Use mongorestore.

Security

39. How do you secure a MongoDB deployment?

• Use strong passwords, enable authentication, configure firewalls, and regularly audit security logs.

40. What is MongoDB's role-based access control (RBAC)?

• A mechanism to control user access to databases, collections, and operations.

Advanced Topics

41. What is the difference between capped collections and uncapped collections?

• Capped collections have a fixed size limit, while uncapped collections can grow indefinitely.

42. What are views in MongoDB?

• Define custom views of data based on queries.

43. Explain the concept of change streams in MongoDB.

• Capture real-time changes to data within a collection.

44. What are transactions in MongoDB?

• Ensure that a set of operations are executed atomically.

45. What is the purpose of the $lookup stage in the aggregation pipeline?

• Perform join operations between collections.

46. How do you handle large datasets in MongoDB?

• Use sharding, indexing, and efficient query patterns.

47. What are some common performance optimization techniques for MongoDB?

• Create appropriate indexes, use efficient query patterns, optimize data modeling.

48. How do you integrate MongoDB with other applications?

• Use MongoDB drivers for various programming languages.

49. What are some common use cases for MongoDB?

• Web applications, mobile applications, IoT, real-time analytics.

50. What are some of the challenges of using MongoDB?

• Complex schema design for some use cases, potential performance issues with large datasets and complex queries.

I hope these questions provide a good starting point for your MongoDB interview preparation. Remember to practice with real-world examples and explore the MongoDB documentation for a deeper understanding.