How does MongoDB handle data storage?
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MongoDB handles data storage using a NoSQL document-oriented model, which is quite different from traditional relational databases. Here's how it works:
Document-Based Storage
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MongoDB stores data as documents in a format called BSON (Binary JSON).
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Each document is a set of key-value pairs, similar to JSON objects.
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Documents are flexible and can have varying fields and structures, allowing schema-less or schema-flexible designs.
Collections
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Documents are grouped into collections, which are analogous to tables in relational databases.
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Collections don’t enforce a fixed schema, so documents within the same collection can differ.
Data Organization
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Each document has a unique _id field used as the primary key.
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Documents can embed other documents or arrays, enabling rich, hierarchical data models.
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Supports references between documents for relationships, but doesn’t require joins like SQL.
Storage Engine
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MongoDB uses a storage engine (default is WiredTiger), which handles data persistence on disk.
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Data is stored in data files, organized into data files, journals, and indexes.
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WiredTiger supports compression and concurrency, improving performance and storage efficiency.
Indexing
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Supports multiple types of indexes (single field, compound, text, geospatial) to optimize query speed.
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Indexes are also stored on disk for fast access.
Data Durability
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Uses a write-ahead logging mechanism called journaling to protect against data loss.
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Data changes are first written to journal files before being applied, ensuring crash recovery.
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