MongoDB
Document store data modeling, aggregation pipeline engineering, indexing, and persistent workflow state.
1 / Document Store Experience
MongoDB provided document-oriented persistence in projects where the data model was naturally hierarchical or semi-structured. Its flexible schema accommodated evolving data shapes during early development phases when the exact data model was still being refined.
2 / Where I Used It
MongoDB appeared in earlier projects — e-commerce applications and social media backends built during training programs — where document-based data models were a natural fit for product catalogs, user profiles, and content feeds. The aggregation pipeline provided powerful data transformation capabilities for analytics queries.
3 / Current Position
My current projects predominantly use PostgreSQL because the combination of relational integrity, JSONB document fields, and pgvector extensions covers most use cases that might otherwise push me toward a document database. MongoDB remains a tool I can use when the use case genuinely calls for a schema-flexible document store.