Do you want to connect JIRA to MongoDB? Are you struggling to find a hassle-free way to establish MongoDB Jira Integration? Well, look no further! Follow our easy step-by-step guide to load your JIRA data to MongoDB in no time. It will help you take charge in a hassle-free way without compromising efficiency. This blog aims at making the data export process as smooth as possible and successfully connect JIRA to MongoDB.
Upon a complete walkthrough of the content, you will be able to carry out a successful data export from JIRA to MongoDB for a fruitful analysis. It will further help you build a customized ETL pipeline for your organization. Through this article, you will get a deep understanding of the tools and techniques being mentioned & thus, it will help you hone your skills further.
Introduction to JIRA
Jira is a popular project management tool used to track the bugs, issues, and progress of various tasks associated with software and mobile applications developed by an organization. Jira provides a powerful and feature-packed dashboard that makes tracking these tasks related to bugs and issues extremely easy. It houses various packages such as JIRA core, software, service desk, etc., each focusing on simplifying tasks such as generic project management and agile project management.
Some key features of JIRA
- Real-time: Jira provides information about data updations in real-time via emails.
- Security: Jira provides a secure bug-tracking system. It supports security-based restrictions to allow only a certain number of individuals or teams to work on a particular bug. Its Default Permission Scheme automatically assigns new projects and tasks to it.
- Robust Integration: JIRA offers strong integration with a variety of tools such as Salesforce, GitHub, Tempo, EasyBI, etc. and makes it extremely easy for IT and software teams to collaborate and resolve issues quickly.
- Agile Development: JIRA provides a smooth experience of working with Scrum and Kanban boards. JIRA is fundamentally based on the Agile model of development and immediately asks users to define the project type as Scrum or Kanban, whenever a new project is created. It even supports a Scrumban (Hybrid of Kanban and Scrum) methodologies to create boards.
For further information on JIRA, you can check the official site here.
Introduction to MongoDB
It is a high-performance document-oriented database that is powered by a NoSQL structure. It makes use of collections (tables) each having multiple documents (records) & allows the user to store data in a non-relational format.
MongoDB stores its data as objects which are commonly identified as documents. These documents are stored in collections, analogous to how tables work in relational databases. MongoDB is known for its scalability, ease of use, reliability & no compulsion to use a fixed schema among all stored documents, giving them the ability to have varying fields (columns).
For further information on MongoDB, you can check the official site here.
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It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. It allows you to focus on key business needs and perform insightful analysis using BI tools.
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- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Working knowledge of Jira.
- Working knowledge of MongoDB.
- A Jira account.
- MongoDB installed at the host workstation.
Using CSV files to connect JIRA to MongoDB
JIRA’s in-built data export option allows users to export data from their applications in various formats such as XML, Excel, CSV, HTML, etc. This Jira to MongoDB migration method requires you to export your JIRA data in a CSV file and then import it into MongoDB either by using the mongoimport command or by using the Studio 3T tool.
You can connect JIRA to MongoDB using the following two steps:
Step 1: Exporting data from JIRA as a CSV file
Launch JIRA on your system and provide your credentials to log in to your account. Once you’ve logged in, select the filter option from the panel on the top of your screen.
Search for the JIRA issue you want to select either by applying necessary filters or selecting it manually. You can do this using the advanced issue search option.
Once you’ve selected the desired JIRA issue, select the export option from the top right corner of your screen.
A dialogue box will now open up, representing a list of formats in which you can export your data.
Choose CSV as the desired format to export your data. You will now be prompted to choose either Excel online or Excel desktop as your desired way of exporting your data. Click on the Excel desktop option to download your data as a CSV file.
This is how you can export your data from JIRA as a CSV file using the in-built export option to connect JIRA to MongoDB.
Step 2: Importing data from the CSV file to MongoDB
Once you’ve exported your data from JIRA as a CSV file, you now need to import this CSV file to MongoDB and successfully connect JIRA to MongoDB. You can do this either writing custom scripts that make use of the mongoimport command or use a tool called Studio 3T to import your CSV data.
This can be implemented using the following two methods:
Using the mongoimport command to import data to MongoDB
Mongoimport is a command-line utility that imports data of different formats such as CSV, JSON, etc. from various sources into your MongoDB instance. Mongoimport runs directly on the MongoDB command line and not on the Mongo Shell.
You can use the mongoimport command to import data from JIRA to MongoDB using the following two steps:
Step 1: Connect to your MongoDB Instance
First, connect with your MongoDB instance. You can do this by specifying the URI as follows:
Replace the parameters with your username, password and provide information about the host and port values as well. In case a user doesn’t specify the port, it automatically uses the default port value of 27017. You can specify them in either of the following formats:
Step 2: Import data from CSV files to MongoDB
Mongoimport is part of MongoDB’s tools package, which is available through the MongoDB Download Center. The tools package must be installed well in advance so that the command-line can be accessed. You can use the mongoimport command as follows:
mongoimport --db= db_name --collection=collection_name --type=csv --headerline --file= file_path
The user must specify the name of the database and collection in which they want to import the data from the CSV file. To access the data file, the user needs to specify the file path to allow the mongoimport command to access the location where the file is stored.
For example, if you want to export your CSV data into a collection called movie_info, in a database called movie, you can use the following command:
mongoimport --db=movie --collection=movie_info --type=csv --header line --file=/opt/backups/movie_info.csv
If you want mongoimport to start searching for data from the very first row in your CSV file, you must include the –header line field in your mongoimport command. Similarly, using the –ignoreBlanks parameter in your mongoimport command ensures that any field containing a null value doesn’t get imported in your desired collection.
For example, if you want to import data from the movie_info.csv file into a collection of your choice and want to avoid including any blank fields, you can use the following command:
mongoimport --db=movie --collection=movie_info --type=csv --file=/example/movie_info.csv --ignoreBlanks
The mongoimport command allows you to specify the desired fields and their data types that you want to import into your MongoDB instance. You can do this by specifying them in the following format:
For example, if you want to incorporate data types along with the field values, you can modify the mongoimport command as follows:
mongoimport --db=users --collection=contacts --type=csv
For further information on using the mongoimport command, you can check the official documentation here.
This is how you can use the mongoimport command to import data from your JIRA CSV data file and successfully connect JIRA to MongoDB.
Using Studio 3T to import data to MongoDB
Studio 3T provides the Import Wizard facility, which helps import data of different formats such as CSV, JSON, etc. from various sources into your MongoDB instance. The process begins by establishing a connection with the desired MongoDB instance and then working on the collection and its documents using the Studio 3T wizard.
Using Studio 3T, you can import CSV files to MongoDB in 2 steps:
Step 1: Using the Import Wizard toolbar
Select and click on the import option, which you can find in the toolbar at the top of your screen. You can right-click on any server or database and then select the import collections option to open the Import Wizard.
Once you’ve clicked on import, a new window will now open up, from where you can select the data type of the file you want to use. Out of the various options available such as JSON, CSV, XML, etc. choose CSV.
This will start the import process for the Jira to MongoDB Migration, which you can easily monitor using the operations window, found in the bottom part of the panel on the left.
Step 2: Importing CSV files into MongoDB
Launch the Studio 3T Import Wizard on your system and select CSV as the format of the file you want to import.
Two new tabs will now open up, from the source options tab, select the import from CSV file option to start configuring your source file. Click on the folder icon to locate your file on your system and select it.
To configure your CSV import, click on the target options tab. Fill the following fields carefully:
- Target Database: Enter the name of the database in which you want to import JIRA data using your CSV file.
- Target Collection: Choose the name of the collection, where you want your CSV data rows to be imported.
- Insertion Mode: Select a mode of inserting your data from the drop-down list.
- Empty Fields: You can choose how to work with fields that don’t have any value. You can either choose to exclude such fields or import these fields as NULL or empty strings.
- Trim Spaces: Using this field, you can choose to trim the leading zeroes, extra spaces.
- Don’t Detect Array: To avoid any headers names that resemble an array such as arr1, arr2, etc. to be considered as an array, check this box.
- Don’t infer document structure: You can use this option to replace all the dots(.) in the header names to an underscore. This is done to prevent them from being considered as an embedded document.
Once you’ve configured your source and target settings, you can select the desired data fields from the import options window and simultaneously check the preview of the JSON data, importing into MongoDB.
CSV files support importing dates in various formats such as ISO, Locale, MDY, DMY, YMD, etc. The Studio 3T Import Wizard automatically detects the correct date format and automatically imports your data into your MongoDB instance in the correct format.
This is how you can connect JIRA to MongoDB by exporting your JIRA data as a CSV file.
Limitations of using CSV Files to Connect Jira to MongoDB
Here are a few limitations you can encounter while using CSV Files to connect Jira to MongoDB:
- JIRA allows users to export only 1000 issues at a maximum to avoid any performance-related issues. The same limitation applies to even bulk operations, query-based changes, etc.
- The mongoimport command often fails to establish a connection and successfully import data in the case of large CSV or JSON files being used to import data to MongoDB.
- The native JIRA export method allows you to export data in various formats, such as XML, CSV, HTML, etc., but often fails to export the data correctly and misses out on certain fields. This increases the chances of missing out on critical information. For example, the team calendars aren’t imported into the XML data file.
This article teaches you how to connect JIRA to MongoDB. It also provides in-depth knowledge about the concepts behind every Jira to MongoDB migration step to help you understand and implement them efficiently. These methods, however, can be challenging especially for a beginner & this is where Hevo saves the day.
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Hevo Data, a No-code Data Pipeline helps you transfer data from a source of your choice in a fully-automated and secure manner without having to write the code repeatedly. Hevo with its strong integration with Jira along with other free data sources & BI tools, allows you to not only export & load data but also transform & enrich your data & make it analysis-ready in a jiffy.
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Tell us about your experience of connecting JIRA to MongoDB! Share your thoughts with us in the comments section below.