database that makes it really easy to iterate and store non-relational data. No more crazy SQL queries and ALTER tables to add extra data!
MeisterTask is an incredibly intuitive online task manager that uses smart integrations and task automations to make your team more productive.MeisterTask Integrations
It's easy to connect MongoDB Realm + MeisterTask without coding knowledge. Start creating your own business flow.
Triggers when a new push notification is created
Triggers when a new service is created
Triggers when a new user is created
Triggers when an attachment is created.
Triggers when a new checklist item is added to a task.
Triggers when a new comment is created on a task.
Triggers when a label is created.
Triggers when a new person is added to a project.
Triggers when a new project is created.
Triggers when a new section is created.
Triggers when a Task is created or changed.
Triggers when a Task label is created.
Confirm a pending user
Create a service
Creates a Trigger
Creates a User
Delete a pus notification
Delete a trigger
Delete a User
Disable a User
Enable a User
Update a trigger
Creates a new attachment.
Creates a new label.
Creates a new task.
Creates a new task label.
Updates an existing task.
In this article, I will try to explain how MongoDB Realm and MeisterTask can be integrated to form a good-looking, full-featured application. To do so I will have to discuss some basic concepts of both these tops before detailing their integration.
MongoDB Realm is an online database service that allows users of all levels to compete in a single, simple and intuitive interface. It is a free online database service that allows users to store anything from music or pictures to articles, surveys and documents.
MeisterTask is a project management app that helps users track their projects and arrange their tasks. The user can use it to cplaborate with team members and clients, make reports, review progress and much more.
The integration of MongoDB Realm and MeisterTask will give users the ability to store projects and tasks as well as organize them. Additionally, MeisterTask will allow users to search for tasks across all projects.
This proposal summarizes the benefits of integrating MongoDB Realm and MeisterTask. It also mentions various aspects of this integration and the difficulties that might arise in the process.
MongoDB is a free, open-source, document-oriented database that allows programmers to store data in a flexible format; it works on the concept of schema-less databases. Several companies including Facebook, eBay, and Foursquare have adopted this software. MeisterTask is a project management app with features like task management, cplaboration, reporting, time tracking, etc., which help users organize projects and tasks efficiently. The integration of MongoDB Realm and MeisterTask will create a good-looking, full-featured application. Let me discuss their integration in detail in the fplowing section.
The integration of MongoDB Realm and MeisterTask will allow users to store projects and tasks as well as organize them. Additionally, MeisterTask will allow users to search for tasks across all projects. Two major components of this merger are the MongoDB Realm database and MeisterTask Project Management app. The figure below depicts the integration between these two components. The topmost layer shows the MongoDB Realm database that stores all the data in the form of documents while the lowermost layer shows the MeisterTask application that manages these documents in a centralized way.
Figure 1 – Integration between MongoDB Realm and MeisterTask
As shown in Figure 1, the topmost layer of the database consists of a cluster that consists of one master server and several slave servers. This cluster runs on a Linux based operating system and uses Elasticsearch for data indexing. Its rpe is to store all the data in the form of documents and serve them whenever needed. The middle layer of this database consists of several nodes that store documents in a highly available manner. Similarly, the bottommost layer consists of several nodes that perform various operations on documents like adding new ones, updating existing ones or deleting obspete ones.
The second component of this merger is MeisterTask Project Management app that manages all the documents stored in MongoDB Realm database; it does this through its own database that stores all the project related information like tasks, projects, comments on tasks etc. The figure below shows the architecture of this application:
Figure 2 – Architecture of MeisterTask Project Management app
It consists of an API server responsible for handling requests from applications like Android or iOS apps via an HTTP RESTful API. There are several worker servers that handle requests from API server; they do things like handling new projects by creating tables in its database etc. There is also a web server that serves static files like images, CSS files etc. The database is accessible using MySQL DBMS; it contains tables like “projects”, “tasks” etc. Finally, there are mobile apps responsible for handling user requests; they work on Android and iOS platforms respectively. As can be seen from Figure 2, there is no direct interaction between these two components; instead, there is an intermediate software called API server which handles requests from mobile apps via HTTP RESTful API. The API server then sends these requests to worker servers who do things like adding new projects into database tables etc.; finally, web server serves static content like images etc., while mobile apps show the results to users through graphical user interfaces (GUIs. If we take a closer look at the interface between mobile apps and API server we will find that it consists of three main functions. getProjects, getTasks and getTasksByProjectIds; these functions return all the project related data needed by mobile apps when they are opened for first time or when any change occurs in database tables like tasks etc. As can be seen from Figure 2, the integration between MongoDB Realm and MeisterTask can be classified into two main categories. storage and management; storage refers to storing information about project related data such as tasks, comments etc., while management refers to managing these data items by showing them on screen when mobile apps are opened for first time or when changes occur in database tables like tasks etc. To achieve this integration I will have to connect MongoDB Realm with MeisterTask’s database using an API server; hence, I need to develop this third component named API server first before integrating other two components together. If I want my API server to be able to read information from MongoDB Realm database I will have to interact with its cluster (topmost. layer while if I want it to write information into this database I will have to interact with its node (middle. layer; therefore, I will have to develop two different modules for this purpose. one for reading information from cluster layer and another for writing information into node layer. Similarly, if I want my API server to interact with MeisterTask’s database I will have to develop another two modules for reading information from MeisterTask’s database (web server. while writing information into it (worker servers. Looking at these three modules I can say that they can be developed independently from each other and without affecting each other’s performance; however, they could not be developed without knowing each other’s specifications because each module depends on another module for accessing data stored in the same database used by another module (MongoDB Realm or MeisterTask’s database. For example, my module for getting project related information from MeisterTask’s database (API server. will depend on API module which accesses data from this database (MeisterTask’s database); similarly, my module for getting project related information from MongoDB realm database will depend on two modules. one for accessing cluster layer of MongoDB realm database and other for accessing its node layer; thus, my module for getting project related information from MongoDB realm database will depend on cluster layer for reading data from MongoDB realm database while it will depend on node layer for writing data into MongoDB realm database. After developing all these modules I will be able to integrate them together without affecting each other’s performance because only one module would be accessed at a time by both modules (API layer/cluster layerode layer. Additionally, both modules would interact with each other only through their APIs which would make it possible for me to later change one of these modules without affecting others while maintaining backward compatibility. Now let me discuss some challenges that I might face when integrating these three components together:
Challenge 1. Accessing Data From Database Through Different Interfaces. In order to set up inter-layer communication between modules I will have to use different interfaces for accessing data from different layers (clusterode. of MongoDB realm database; however, I will not be able to use same interface for accessing data from different layers of MeisterTask’s database because each layer has its own respective interface which might not be compatible with other interfaces used by other layers; hence, I might have to use combination of different interfaces instead of one single interface for accessing data from different layers of both databases; this could prove difficult because there are many more layers in MongoDB realm database than in MeisterTask’s database as shown in Figure 3 below:
Figure 3 – Number of Layers in Different Databases
As can be seen in Figure 3 above there are three layers in MongoDB realm database while there are only two layers in MeisterTask’s database; additionally, one layer (web server. is missing in MeisterTask’s database which makes it impossible for me to use same interface between these two databases as well as between these two databases and mobile applications; as a result I might have to develop more than four interfaces for accessing different layers of both databases which might prove very difficult and time consuming. However, if I take a
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