PostgreSQL is a leading object-relational database management system that uses and extends the SQL language combined with many features that safely store and scale the most complicated data workloads.
MongoDB is an open-source document-based database management tool that stores data in JSON-like formats. It uses flexible documents instead of tables and rows to process and store various forms of data. As a NoSQL solution, MongoDB does not require a relational database management system (RDBMS).MongoDB Integrations
PostgreSQL + Google SheetsCreate rows in Google Sheets for new PostgreSQL custom query matches. Read More...
PostgreSQL + AsanaCreate Asana tasks for new PostgreSQL custom query matches Read More...
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MongoDB + Google SheetsCreate new rows in Google Sheets for new MongoDB documents Read More...
It's easy to connect PostgreSQL + MongoDB without coding knowledge. Start creating your own business flow.
Triggered when you add a new column.
Triggered when you add a new row.
Triggered when new rows are returned from a custom query that you provide. Advanced Users Only
Triggers when you add a new collection.
Triggers when you add a new database.
Triggers when you add a new document to a collection.
Triggers when you add a new field to a collection.
Adds a new row.
Updates an existing row.
Create a new document in a collection of your choice.
PostgreSQL is an object-relational database management system that includes a relational database, as well as an object oriented database. PostgreSQL can be used to store data from multiple types of applications, such as web apps and databases. It is a server-based relational database that is a feature rich database management software or RDBMS. The primary function of a relational database is to store data, and to retrieve it in specified formats.
MongoDB is a document-oriented database, which means it stores data in documents rather than tables. MongoDB is similar to the NoSQL database because unlike most other relational databases, the primary storage in MongoDB is not based on tables and rows, but on documents and JSON objects.
The first approach for integrating PostgreSQL and MongoDB is by using a database connector. A database connector is a software that allows you to connect PostgreSQL with MongoDB. It allows you to transfer data from PostgreSQL to MongoDB and vice versa. An example of a database connector is pymongo.
There are several advantages in integrating PostgreSQL and MongoDB using a database connector. First, using this method, you only need to use one driver for both the PostgreSQL and MongoDB databases. This will save time and effort for developers. Second, you can perform the integration using the same query language, which saves you more time and effort. Third, this method allows you to use some of the advanced features of PostgreSQL in MongoDB, such as triggers, views, functions and dump/restore. However, using this method has its disadvantages too. Using one driver for both databases will not be able to translate all the ones that are specific to either PostgreSQL or MongoDB.
Integration of PostgreSQL and MongoDB offers several benefits to enterprises:
It can help businesses start operating at lower costs because it reduces hardware and software expenses. Having two databases running on one system will reduce costs because there will be less hardware required, as well as less maintenance costs since there will be fewer components. This will also help businesses save money when modernizing legacy systems because they can easily switch between the two databases depending on the task at hand.
It can help companies achieve high performance at an affordable cost since you only need to purchase one license for your database management software. Therefore, your company’s budget can be allocated to maintaining existing infrastructure components, improving them or purchasing new ones. You will not have to spend extra money on buying additional licenses for your database management software. This can save your company thousands of dplars each year. Having two databases running on one system will improve performance because there will be less latency due to accessing information from different databases using different query languages.
It allows companies to expand their business reach fast because it is easier to deploy applications in the cloud since you only need one database management software license for both PostgreSQL and MongoDB. This will save companies time and money, allowing them to focus more on creating new products or improving the existing ones instead of buying additional licenses for their database management software. There are many cloud services that support MongoDB, so integrating PostgreSQL and MongoDB through a database connector will allow your company to easily port their existing applications into the cloud without much effort. Deploying applications in the cloud helps you scale up quickly when your business expands to other countries without increasing your costs significantly. This can be achieved by simply adding more machines to your cloud service provider’s cluster while paying only for the resources that are being utilized instead of buying more hardware and software licenses for your network servers or physical computers.
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