#Mongodb compass filter date upgrade#
#Mongodb compass filter date code#

Note that types can be specified using either a number or a string alias. When present, the phone number and email address are strings.The document contains a phone number and/or an email address.The year of birth is no later than 1994.For others, it can be a little intimidating.Īs an example, the following snippet adds validations to the contacts collection that validates: That the value falls within a given rangeįurther, it may be necessary to combine these checks – for example that the document contains the user’s name and either their email address or phone number, and if the email address does exist, then it must be correctly formed.Īdding the validation checks from the command line is intuitive to developers or DBAs familiar with the MongoDB query language as it uses the same expression syntax as a find query to search the database.That the value is in a particular format (e.g., regular expressions can be used to check if the contents of the string matches a particular pattern).If an attribute does exist, that it is of the correct type.For any attribute it might be appropriate to check: Validating Documents in MongoDBĭocument Validation provides significant flexibility to customize which parts of the documents are and are not validated for any collection. MongoDB Compass 1.5 allows users to view, add, and modify document validation rules through its GUI, making them more accessible to both developers and DBAs. Adding and viewing validation rules required understanding the correct commands to run from the mongo shell’s command line. To address the challenges discussed above, while at the same time maintaining the benefits of a dynamic schema, MongoDB 3.2 introduced document validations.

#Mongodb compass filter date code#

To date, this resulted in developers building their own validation logic – either within the application code (possibly multiple times for different applications) or by adding middleware such as Mongoose. If one of the vendors alters the format of its product catalog, global catalog searches could fail. Development teams from different companies may be working with the same collections misunderstandings about what data should be present can lead to issues.Īs an example, an e-commerce website may centralize product catalog feeds from multiple vendors into a single collection.Development teams working on different applications can be spread over multiple sites, which means that a clear agreement on the format of shared data is important.Different development teams can work with the same data, each needing to know what they can expect to find in a particular collection.Many projects reach a point where it’s necessary to enforce rules on what’s being stored in the database – for example, that for any document in a particular collection, you can be certain that specific attributes are present in every document. For business leaders, the application gets launched much faster, and new features can be rolled out more frequently.

#Mongodb compass filter date upgrade#

Operations teams appreciate the fact that they don’t need to perform a time-consuming schema upgrade operation every time the developers need to store a different attribute.

One of MongoDB’s primary attractions for developers is that it gives them the ability to start application development without first needing to define a formal schema. This makes it easy to create and modify rules that ensure that all documents written to a collection contain the data you expect to be there. This post looks at a new feature in MongoDB Compass 1.5 (in beta at the time of writing) which allows document validation rules to be added from the GUI rather from the mongo shell command line. Adding Document Validation Rules Using MongoDB Compass 1.5