In the ever-evolving landscape of database management systems, two dominant paradigms have stood out: SQL (Structured Query Language) databases and NoSQL databases. SQL databases offer a structured, tabular format that’s great for handling structured data and complex queries, while NoSQL databases excel at handling unstructured or semi-structured data with high scalability and flexibility. However, the lines between these paradigms have started to blur with the advent of technologies like MongoDB Atlas SQL, which aims to bring the best of both worlds together. In this article, we will delve into the world of MongoDB Atlas SQL, exploring its features, benefits, and use cases.
What is MongoDB Atlas SQL?
MongoDB Atlas SQL is a fully managed, cloud-native, and multi-cloud SQL service that enables you to query and analyze data stored in MongoDB using the SQL language. It serves as a bridge between the traditional relational SQL databases and the NoSQL nature of MongoDB. It allows you to leverage your SQL skills and tools to interact with and extract insights from your MongoDB data without needing to learn a new query language or migrate your data to a different database system.
Scalability and Flexibility
Business environments are constantly evolving, and your CPM software must be able to adapt to changing requirements. Look for solutions that offer flexibility and scalability to accommodate future growth, mergers, acquisitions, and changes in business processes. Cloud-based CPM software can provide the necessary scalability, allowing your organization to add users and functionalities as needed without significant disruptions.
Seamlessly Integrate with Existing Systems
To maximize the value of your CPM software, ensure it seamlessly integrates with your existing financial systems, enterprise resource planning (ERP) software, and other data sources. This integration streamlines data flows, eliminates manual data entry, and ensures data accuracy across the organization. Look for software that supports data connectors or APIs to enable smooth data exchange between systems.
Key Features
- SQL Compatibility: MongoDB Atlas SQL supports the SQL language, (SQL-92 Dialect) which means that users familiar with SQL can easily start querying their MongoDB data without having to learn a new query language. This is especially beneficial for organizations that have existing SQL expertise within their teams.
- Schema Flexibility: Unlike traditional relational databases, MongoDB’s native schema-less structure enables the storage of unstructured or semi-structured data. MongoDB Atlas SQL retains this flexibility while allowing you to query the data using SQL syntax.
- Fully Managed Service: MongoDB Atlas SQL is a fully managed service, which means that database provisioning, scaling, backups, and maintenance tasks are handled by MongoDB Atlas. This offloads the operational overhead from your team, allowing them to focus on data analysis and application development.
- Performance: MongoDB Atlas SQL leverages the underlying performance capabilities of MongoDB, such as sharding and indexing, to deliver high-speed queries on large volumes of data. This performance ensures that your data analysis remains efficient even as your data scales.
- Security and Compliance: As part of MongoDB Atlas, Atlas SQL inherits the security features offered by MongoDB. This includes encryption at rest, in transit, and fine-grained access controls. It also helps organizations adhere to compliance standards by providing auditing and monitoring capabilities.
- Integration: MongoDB Atlas SQL seamlessly integrates with popular analytics and business intelligence tools like Tableau, Power BI, and Looker, enabling users to visualize and gain insights from their MongoDB data.
Which problems does Atlas SQL solve?
Some BI Tools such as Tableau and Power BI can’t connect to a MongoDB database directly and extracting and moving large datasets around is costly and slow, that’s where Atlas SQL comes into play, by activating Atlas SQL in your MongoDB database deployed in Atlas you don’t need to create another relational database in other to allow your users to use these BI Tools to graph, visualize and report on your Atlas data.
How does it work?
There are four main components here:
- The database is hosted at MongoDB Atlas Data Platform.
- The Atlas SQL interface
- The Connector and/or SQL Driver used by the BI Tool
- BI Tool
You need to enable Atlas SQL in your MongoDB database once you have it enabled you can use the custom connection string generated by Atlas in your BI Tool to access the MongoDB database.
Tableau Requirements
Different BI Tools have different requirements. For this blog post, we will be using Tableau and it requires two files to be downloaded and moved:
1 – The JDBC Driver, available at: https://www.mongodb.com/try/download/jdbc-driver after downloading, move the downloaded .jar file into the appropriate directory for your operating system:
Windows
C:\Program Files\Tableau\Drivers
MacOS
~/Library/Tableau/Drivers
2 – The Tableau Custom Connector, available at: https://www.mongodb.com/try/download/tableau-connector. After downloading, Move the downloaded taco file into the appropriate directory for your operating system:
Windows
C:\Documents\My Tableau Repository\Connectors
MacOS
~/Documents/My Tableau Repository/Connectors
Kick Start
The first step is to open your database deployment and under “ATLAS SQL” click “Connect”:
In the first time you need to create the new connection string, click “Create”:
In step 3 select the driver, in our case, it’s Tableau Connector:
In step 4 select the database you want to connect. Once it’s done you just need to copy & paste the string into your BI Tool, for Tableau find the option “MongoDB Atlas by MongoDB” under the connect menu:
Now paste the connection string you just copied and provide the database name you want to connect and valid credentials then click “Sign In”:
Once it’s done you can see your MongoDB as a relational database inside Tableau:
Conclusion
The database landscape is evolving, and technologies like MongoDB Atlas SQL are a testament to the industry’s desire to bridge the gap between SQL and NoSQL paradigms. By offering a familiar SQL interface to interact with MongoDB’s flexible data model, MongoDB Atlas SQL empowers organizations to unlock insights from their data without compromising on scalability or performance. Whether you’re looking to integrate SQL and NoSQL databases or leverage SQL skills for MongoDB data analysis, MongoDB Atlas SQL offers a powerful solution worth considering. As data requirements continue to grow in complexity, tools like MongoDB Atlas SQL provide a stepping stone toward a more unified and adaptable data ecosystem.
