Document-oriented databases store data as self-contained documents, typically in JSON or BSON format. Unlike relational databases that spread data across multiple tables with foreign keys, document…
Read more →A MongoDB replica set consists of multiple mongod instances that maintain identical data sets. The architecture includes one primary node that receives all write operations and multiple secondary…
Read more →MongoDB’s flexible schema allows you to structure related data through embedding (denormalization) or referencing (normalization). Unlike relational databases where normalization is the default,…
Read more →• Sharding distributes data across multiple servers using a shard key, enabling horizontal scaling beyond single-server limitations while maintaining query performance through proper key selection
Read more →• MongoDB transactions provide ACID guarantees across multiple documents and collections since version 4.0, eliminating the need for application-level compensating transactions in complex operations
Read more →The aggregation pipeline is MongoDB’s answer to complex queries. Think of it as a Unix pipe for documents.
Read more →The MongoDB aggregation framework operates as a data processing pipeline where documents pass through multiple stages. Each stage transforms the documents and outputs results to the next stage. This…
Read more →• Single-field indexes optimize queries on one field, while compound indexes support queries on multiple fields with left-to-right prefix matching—order matters significantly for query performance.
Read more →Add the MongoDB Spark Connector dependency to your project. For Spark 3.x with Scala 2.12:
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