Latest MongoDB Interview Questions & Answers (2025):

1. Does MongoDB support ACID transactions across multiple documents/collections?
Yes, since version 4.0, MongoDB supports multi-document ACID transactions for replica sets, and from 4.2 onwards, for sharded clusters. Use startSession() and withTransaction() in drivers or shell to manage atomicity and rollbacks.​

2. What is the aggregation pipeline and why is it powerful?
Aggregation pipelines allow data transformation via multiple stages ($match, $group, $project, $sort, $limit, etc.), supporting operations like grouping, filtering, and calculating metrics, similar to SQL GROUP BY but with greater flexibility and scalability.​

3. Explain sharding vs. replication.
Replication (replica sets) provides high availability; data is copied to multiple nodes. Sharding enables horizontal scaling by splitting data across multiple servers (“shards”) to manage massive datasets and concurrent workloads.​

4. What are TTL (Time-To-Live) indexes?
TTL indexes automatically remove expired documents after a predefined time period, great for logs and session data cleanup.​

5. What is the WiredTiger storage engine?
WiredTiger is the default since MongoDB 3.2, offering document-level locking, compression, and improved concurrency. It replaced MMAPv1 for better performance under heavy loads.​

6. Compound indexes – when should you use them?
Compound indexes index multiple fields in a specified order, improving query speed for filtering/sorting involving several fields.​

7. What’s the difference between $lookup and $graphLookup in aggregations?
$lookup is used for left outer joins between collections. $graphLookup performs recursive searches—useful for hierarchical data.

8. Describe write concern and read concern.
Write concern determines acknowledgment required for write ops (e.g., “majority” means most replicas); read concern ensures a consistent snapshot for reads.​

9. How do you optimize slow MongoDB queries?

  • Create relevant indexes.
  • Project only needed fields.
  • Use the aggregation pipeline for complex querying.
  • Analyze execution plans via explain().
  • Split large documents when possible.​

10. What is the upsert operation, and where is it used?
Upsert updates a matching document or inserts a new one if it doesn’t exist—commonly used in update workflows.​

11. What is the role of Mongos in sharded clusters?
mongos routes queries from clients to appropriate shards, providing a transparent interface for sharding.​

12. How do you perform text search in MongoDB?
Create a text index and use the $text query operator for searching keywords in string fields.​

13. How do you connect a Node.js app to MongoDB using Mongoose?
Install Mongoose, define schemas, connect using mongoose.connect(), and interact via model methods (find(), save(), etc.).​

14. What steps do you follow migrating data from SQL to MongoDB?
Map relational tables to documents, export as JSON/BSON, import using mongoimport, validate and optimize indexed/query fields.​

15. How do you monitor MongoDB performance?
Use Atlas/Ops Manager dashboards, monitor with db.currentOp(), analyze logs, set alerts for replica set failover, and use slow query logs.​

Scenario-Based & Advanced Questions (2025 Focus):

  • Troubleshoot replica set failover steps, memory spikes, timeouts.
  • How do you handle schema changes with evolving apps?
  • Describe strategies for scaling MongoDB in high-traffic use cases.
  • Node.js and MongoDB validation and error handling.

Bangalore Job Seekers Tips for 2025:

  • Prepare hands-on aggregation pipeline tasks (real-world data questions).
  • Know latest indexing, scaling, monitoring, Atlas/cloud features.
  • Practice schema migration and performance tuning.
  • Stay up-to-date with MongoDB documentation and new features.

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