The key challenge in data modeling is balancing the needs of theapplication, the performance characteristics of the database engine, andthe data retrieval patterns. When designing data models, alwaysconsider the application usage of the data (i.e. queries, updates, andprocessing of the data) as well as the inherent structure of the dataitself.

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  1. TablePlus is a young project, we fix bugs and add new features every day, then put them together in a new update released at the end of week/month.
  2. MongoDB Exercises, Practice, Solution: MongoDB is a free and open-source cross-platform document-oriented database. Classified as a NoSQL database, MongoDB avoids the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas, making the integration of data in certain types of applications easier and faster.
  3. Import Oracle Database Tables into MongoDB Database. Import Oracle Database Tables into MongoDB Database.
  4. The MEAN stack is used to describe development using MongoDB, Express.js, Angular.jS and Node.js. In this tutorial I will show you how to use Express.js, Node.js and MongoDB.js. We will be creating a very simple Node application, that will allow users to input data that they want to store in a MongoDB database.

In MongoDB Collection refers to table in RDBMS view. Before discussing the collection creation we need to know the difference between collection and cappedCollection.

Flexible Schema¶

Unlike SQL databases, where you must determine and declare a table'sschema before inserting data, MongoDB's collections, by default, do not require their documents to have the same schema. That is:

  • The documents in a single collection do not need to have the same setof fields and the data type for a field can differ across documentswithin a collection.
  • To change the structure of the documents in a collection, such as addnew fields, remove existing fields, or change the field values to anew type, update the documents to the new structure.

This flexibility facilitates the mapping of documents to an entity oran object. Each document can match the data fields of the representedentity, even if the document has substantial variation from otherdocuments in the collection.

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In practice, however, the documents in a collection share a similarstructure, and you can enforce document validation rules for a collection during update and insertoperations. See Schema Validation for details.

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Document Structure¶

The key decision in designing data models for MongoDB applicationsrevolves around the structure of documents and how the applicationrepresents relationships between data. MongoDB allows related data tobe embedded within a single document.

Embedded Data¶

Embedded documents capture relationships between data by storingrelated data in a single document structure. MongoDB documents make itpossible to embed document structures in a field orarray within a document. These denormalized data models allowapplications to retrieve and manipulate related data in a singledatabase operation.

For many use cases in MongoDB, the denormalized data model is optimal.

See Embedded Data Models for the strengths and weaknesses ofembedding documents.

References¶

References store the relationships between data by includinglinks or references from one document to another. Applications canresolve these references toaccess the related data. Broadly, these are normalized data models.

See Normalized Data Models for the strengths and weaknesses ofusing references.

Atomicity of Write Operations¶

Single Document Atomicity¶

In MongoDB, a write operation is atomic on the level of a singledocument, even if the operation modifies multiple embedded documentswithin a single document.

A denormalized data model with embedded data combines all related datain a single document instead of normalizing across multiple documentsand collections. This data model facilitates atomic operations.

When a single write operation (e.g.db.collection.updateMany()) modifies multiple documents,the modification of each document is atomic, but the operation as awhole is not atomic.

When performing multi-document write operations, whether through asingle write operation or multiple write operations, otheroperations may interleave.

For situations that require atomicity of reads and writes to multipledocuments (in a single or multiple collections), MongoDB supportsmulti-document transactions:

  • In version 4.0, MongoDB supports multi-document transactions onreplica sets.
  • In version 4.2, MongoDB introduces distributed transactions,which adds support for multi-document transactions on shardedclusters and incorporates the existing support formulti-document transactions on replica sets.

For details regarding transactions in MongoDB, see theTransactions page.

Multi-Document Transactions¶

For situations that require atomicity of reads and writes to multipledocuments (in a single or multiple collections), MongoDB supportsmulti-document transactions:

  • In version 4.0, MongoDB supports multi-document transactions onreplica sets.
  • In version 4.2, MongoDB introduces distributed transactions,which adds support for multi-document transactions on shardedclusters and incorporates the existing support formulti-document transactions on replica sets.

For details regarding transactions in MongoDB, see theTransactions page.

In most cases, multi-document transaction incurs a greaterperformance cost over single document writes, and theavailability of multi-document transactions should not be areplacement for effective schema design. For many scenarios, thedenormalized data model (embedded documents and arrays) will continue to be optimal for yourdata and use cases. That is, for many scenarios, modeling your dataappropriately will minimize the need for multi-documenttransactions.

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For additional transactions usage considerations(such as runtime limit and oplog size limit), see alsoProduction Considerations.

Data Use and Performance¶

When designing a data model, consider how applications will use yourdatabase. For instance, if your application only uses recentlyinserted documents, consider using Capped Collections. Orif your application needs are mainly read operations to a collection,adding indexes to support common queries can improve performance.

See Operational Factors and Data Models for more information on theseand other operational considerations that affect data model designs.

Learn More¶

MongoDB.live 2020 Presentations¶

To learn how to incorporate the flexible data model into your schema,see the following presentations from MongoDB.live 2020:

  • Learn about entity relationships in MongoDB and examples of theirimplementations withData Modeling with MongoDB.
  • Learn advanced data modeling design patterns you can incorporateinto your schema withAdvanced Schema Design Patterns.

Application Modernization Guide¶

For more information on data modeling with MongoDB, download theMongoDB Application Modernization Guide.

The download includes the following resources:

  • Presentation on the methodology of data modeling with MongoDB
  • White paper covering best practices and considerations formigrating to MongoDB from an RDBMS data model
  • Reference MongoDB schema with its RDBMS equivalent
  • Application Modernization scorecard

In MongoDB Collection refers to table in RDBMS view. Before discussing the collection creation we need to know the difference between collection and cappedCollection.

_'/> Collection Vs. CappedCollection

snoCollectionCappedCollection
1A group of documentsA group of documents (one of the
flavor of collection)
2Doesn’t have limitation on sizeIt’s a fixed size collection.

CappedCollection:-
A fixed-sized collection that automatically overwrites its oldest entries when it reaches its maximum size.

_'/> How to Create Collections

We can create collection mainly in two ways

  1. Using db.createCollection() method
  2. Inserting document to a Collection which is not created yet.

db.createCollection():-

db.createCollection(name, options) creates a new collection explicitly. In general MongoDB creates a collection implicitly when the collection is first referenced in a command

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When to use db.createCollection()

  1. If we need a cappedCollection.
  2. If we want a collection with documentValidation(field level conditions like EmailId with @symbol, age as numeric, mobile number with x places etc..)

Basic Syntax of db.createCollection()
db.createCollection(name, options)
The db.createCollection() method has the following parameters:

ParameterTypeDescription
namestringThe name of the collection to create.
optionsdocumentOptional. Configuration options for creating a capped collection or for preallocating space in a new collection.

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Some of the main options are listed below

FieldTypeDescription
cappedbooleanOptional. To create a capped collection, specify true. If you specifytrue, you must also set a maximum size in the size field.
sizenumberOptional. Specify a maximum size in bytes for a capped collection. Once a capped collection reaches its maximum size, MongoDB removes the older documents to make space for the new documents. The size field is required for capped collections and ignored for other collections.
maxnumberOptional. The maximum number of documents allowed in the capped collection. The size limit takes precedence over this limit. If a capped collection reaches the size limit before it reaches the maximum number of documents, MongoDB removes old documents. If you prefer to use the max limit, ensure that the size limit, which is required for a capped collection, is sufficient to contain the maximum number of documents.
validatordocumentOptional. Allows users to specify validation rules or expressions for the collection. For more information, see Document Validation.
validationActionstringOptional. Determines whether to error on invalid documents or justwarn about the violations but allow invalid documents to be inserted.

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Example Collections :-

  • Collection Creation without any options
  • CappedCollection Creation
    (Need to creation a collectionfor this purpose
    1. Which holds only 1 Document(row)
    2. If the new document came automatically need to overwrite.
    )
    If you observe the above insert result old record (~xyz.tmp) is overwritten with new file due to capped concept.
    We will discuss insert() in next session clearly.
    Inserting document to a Collection which is not created yet:-
    MongoDB creates a collection implicitly when the collection is first referenced in a command from any insert() related methods. Means db.tempdoc.insert({snofield:1}) will create a collection named tempdoc if not exist.
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