Five years ago, MongoDB detailed new enhancements that enabled it to work with standard relational reporting tools like Cognos, Tableau, and Business Objects. That's great but it's not perfect. As a result, a number of analytical tools continue to thrive, solving for the challenge of dealing with MongoDB's NoSQL-ness. To illustrate, let's consider a scenario from our time.
Lack of structure is a doubled-edge sword. Just ask anybody parenting school-age children during a pandemic. On one hand, structure restricts us from the organic flow inherent to our lives. On the other hand, it ensures that we get what we expect at the end of the day.
The same is true with data. MongoDB's acceptance of flexibly-structured data in collections makes it easy to capture data as the context around the data changes. However, this comes at a cost—one that's all too familiar to the analyst who have dealt with MongoDB: it can be a real headache to analyze data after it is stored.
To solve this problem, there are different tools for different jobs.. In this post, we'll discuss the analytical jobs at hand and compare the tools to complete them.
MongoDB analytics tools
You probably have lots of company data stored and shelved. But it’s spread about, making it tricky to meaningfully gather insights into the business’s inner workings.
NoSQL databases emerged as a solution to big data issues arising from a usage influx of web apps and the Internet in general. While NoSQL databases are the best fix for big data needs, relational databases remain the gold standard for transaction-oriented data. When a business needs to analyze both data types together, integrating NoSQL and relational databases becomes crucial.
A 2017 conference paper on this very topic concluded that there are two approaches for integrating NoSQL and relational databases: “native” and “hybrid” solutions. But from the viewpoint of users, the real value of data—whether stored in NoSQL or relational databases—depends on how well it can be used to better understand their businesses, supplier, and customers. In today’s dynamically digitalized world, data is omnipresent, coming from social networks, transactional systems, websites, etc. and users do not want limitations in what sources they can actually analyze.
One interesting innovation is self-service business intelligence (BI) integrations that allow users outside of the IT department to create their own reports and visually engaging charts in an easy-to-use, unbreakable system. This boosts both operational efficiencies and data mining by freeing up the IT department while allowing non-technical users to independently query, access and analyze company data.
Organizations that manage both relational and NoSQL databases often suffer from these reporting issues:
Challenges like these are why it's so important to find an analytics tool that enables you to work with MongoDB data. Thankfully, there are plenty of options to choose from—it's just a matter of figuring out which one suits your particular purposes.
Let’s start with a free client: MondoDB Compass is the GUI for MongoDB and has been free to all users for some time now on Github under the SSPL. This visual editing tool allows you to understand and analyze data sets without a formal education in MongoDB query syntax and addresses MongoDB’s inability to natively support SQL.
You can use Compass to manage indexes, optimize query performance, and intelligently undertake document validation. CRUD (create, read, update, and delete) functionality makes it simple to interact: quickly edit/clone/delete existing documents or insert new ones in a few clicks. Compass provides an overall fast overview into your data’s behavior and is designed to fix performance issues, a Swiss army knife.
MongoDB Compass price: free, only works with MongoDB.
With a native ETL for MongoDB, even non-technical users can set up a pipeline into Panoply in minutes. The data is automatically transformed into tables that fit Panoply’s relational model, which enables SQL querying and connections to a variety of popular analytics and BI tools.
Panoply price: see all pricing options; a free trial is available.
Non-technical users can access analytics code-free: Knowi’s self-service BI has natural language capabilities that let users ask questions in English. For business teams, data scientists and data engineers, its native integrations are well suited for iterative work and enable the creation of optimal datasets in a matter of days, instead of weeks. Knowi provides a hassle free, “no ETL” approach to unifying big, messy data.
Knowi price: Quotation-based, free trial with no credit card required.
Customizable, user-based, shareable dashboards work in real-time at the speed of your business in a web-based platform that works on any device and inherits your platform’s security and privacy model in order to be standards compliant. Izenda is capable of seamlessly embedding into existing platforms and workflows.
Izenda price: $999 - $1999/month based on data size and features
Managers can visually review business performance, streamlining the detection of opportunities, trends, and operations. General users can efficiently keep up to date with smart data entry using functions that include data validation and temporary storage. Meanwhile, IT teams get simple deployment and integration, as FineReport’s APIs streamline the customization process of reporting systems.
FineReport price: Quotation-based plan based on function and user-size
Users can monitor the health of databases with 24/7 extreme data granularity and customizable dashboards for critical analytics. With SolarWinds, you can also dig into the reasons behind performance issues in open-source databases using DBAs with helpful before and after comparisons, DevOps features, and patented adaptive fault detection.
SolarWinds Database Performance Monitor price: Starts at $2,840
ClusterControl is your go-to solution if you need a central interface for operating one or multiple clusters and can manage whole clusters rather than separate DB nodes. It’s also able to automate operations like node health and performance checks and management tasks such as rolling starts and cluster-wide configuration changes.
ClusterControl price: Community edition is free
A final, bonus addition to this list is MongoJS Query Analyzer, which works as an interactive JavaScript editor. Result sets are viewable as a tree hierarchy, text history, pivot and grid results and users can save in even more formats like XML, HTML, Excel worksheets, and so on.
A rich tool with a great set of features that includes autocompletion support and syntax highlighting, MongoJS Query Analyzer is unique in its use of JS commands.
MongoJS Query Analyzer price: Offered by Aqua Data Studio, starts at $499.
With simple setup and low-maintenance pipelines and storage that can handle both relational and unstructured data, Panoply is the perfect solution for businesses that want sophisticated analytics without going deep into data engineering.
Start your 14 day trial now to experience its ease of use for yourself, or get a personalized demo to see how Panoply can work for your business.