Feature image Top 10 noSQL Analytics & Reporting tools

Top 10 NoSQL Analytics & Reporting Tools

By Laurent Mauer · November 16, 2022 · 11 min read

NoSQL Database is a non-relational Data Management System that does not require a fixed schema. It avoids joins, and is easy to scale. The major purpose of using a NoSQL database is for distributed data stores with humongous data storage needs. NoSQL is used for Big data and real-time web apps. For example, companies like Twitter, Facebook and Google collect terabytes of user data every single day.

NoSQL database stands for “Not Only SQL” or “Not SQL.” Though a better term would be “NoREL”, NoSQL caught on. Carl Strozz introduced the NoSQL concept in 1998.

Traditional RDBMS uses SQL syntax to store and retrieve data for further insights. Instead, a NoSQL database system encompasses a wide range of database technologies that can store structured, semi-structured, unstructured and polymorphic data

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, integrate NoSQL, get reports of the data, NoSQL Tools comes into the picture.

NoSQL Reporting

Database reporting tools are the reporting software that helps you directly generate reports of the data from the database or the data warehouse you use. There are two types of databases used in the company or organizations: relational databases and NoSQL data sources. 

The relational database is built on the relational model. It deals with the data in the database using set algebra and other mathematical methods. In short, a relational database is a database composed of several two-dimensional tabular that can be connected. Oracle, DB2, Microsoft SQL Server, Microsoft Access, MySQL are the popular relational databases nowadays. 

They are easy to use and maintain. Database reporting tools rely on connections to a relational database management system via JDBC, JNDI or ODBC. After connecting, you can use SQL to query data and then generate reports.

When storing large volumes of data without structure, or using cloud computing and storage, NoSQL databases might be preferable. NoSQL databases do not require tables with a fixed set of columns, avoid JOINs, and typically support horizontal scaling. For instance, the MongoDB database is the leader in NoSQL databases, and his use is becoming more widespread. Database reporting on NoSQL data sources that require either a customized SQL connector or database plugin for accessing data.

NoSQL analytics and Reporting Tools

The difficulty of integrating relational and NoSQL reporting

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:

The standard method of integrating SQL and table-based tools like Excel for reporting is inaccurate and time-consuming.

Difficulty matching up data from SQL and NoSQL databases.

An inability to keep up with reporting demands as markets change.

A reduced global data perspective from the lack of a cohesive reporting management portal.

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.

Free & low-code tools (NoSQL)

1. MongoDB Compass

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.

2. Panoply (SQL/NoSQL)

Panoply works with MongoDB as well as relational data sources.Panoply is a cloud data platform that enables both syncing and storage of SQL and NoSQL data, making it easy for users to gather data from every corner of their companies into a single source of truth (SSOT).

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.

3. Knowi (NoSQL)

Knowi is a NoSQL BI tool for MongoDBKnowi is a business intelligence solution for instantly bridging relationships with any data, structured or unstructured, with no need to transform or migrate. It’s the only full stack analytics platform with built-in integrations for all of the popular NoSQL data stores, as well as cloud APIs and relational data sources.

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.

4. Izenda (SQL/NoSQL)

Izenda is a BI tool for MongoDBIzenda provides a code-free connection to web services and databases for reporting, dashboards, and visualizations. Users can create complex queries in plain English using self-service BI technologies, essentially making it a search engine for your business data.

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.

5. FineReport (SQL/NoSQL)

FineReport is a reporting tool for MongoDBFineReport is a frontrunner in enterprise web reporting and BI software, designed for fast access to data anytime anywhere. Used by over 8,000 companies, it’s popular with users looking for a drag-and-drop interface.

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.

Database health monitors

6. SolarWinds Database Performance Monitor

SolarWinds is a db performance monitor for MongoDBSolarWinds Database Performance Monitor is a cross-platform performance monitoring and tuning tool that supports cloud databases (its companion, the Database Performance Analyzer, supports on-premise).

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.

7. ClusterControl

ClusterControl is a management tool for MongoDBClusterControl is a database management tool for scaling, monitoring, and deploying database clusters. It offers a simple web graphical interface for autoscaling, monitoring, and managing cluster databases with Galera Cluster, MySQL Cluster, and MySQL Replication support.

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.

Javascript GUI

8. MongoJS Query Analyzer

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.

Reporting Tools

9. FineReport 

FineReport is a database reporting software that supports broad data sources, including relational databases such as SQL Server, MySQL, Oracle; text data sources, multidimensional databases, NoSQL data sources, built-in datasets, and other program data sources.

Database Reporting tool

Broad Data Source Report

The data connection is convenient. FineReport can connect data sources through various channels, including direct connection to the database via JDBC, sharing database connection with the application server via JNDI or connection to the SAP system via JCO. It takes seconds and requires no messy scripting or coding.

Database Reporting

FineReport also supports extracting and combining data across databases and tables, and easy to integrate data from ERP/OA/MES and other enterprise systems in a single platform, which breaks the information silos in the organizations.

10. Tableau

Tableau is the most popular BI tool with visualization capabilities and shining reporting. 

It offers a powerful visualization engine and an easy-to-use interface to quickly turn data into impressive charts, reports, and dashboards. Additionally, the software provides hundreds of visualization customization options and interaction techniques at users’ disposal.

On top of that, Tableau has a thriving community and forum where you can find numerous videos, guides, and tips.

The only advantage is the cost is high, and the flexibility is low that it is difficult to customize or embedded into companies’ IT landscape.

Highlights: ease of use, competitive visualization effects, unrivaled community

Conclusion

At RestApp, we’re building a Data Activation Platform for modern data teams with our large built-in library of connectors to databases data warehouses and business apps.

We have designed our next-gen data modeling editor to be intuitive and easy to use.

If you’re interested in starting with connecting all your favorite tools, check out the RestApp website or try it for free with a sample dataset.

Discover the next-gen end-to-end data pipeline platform with our built-in No Code SQL, Python and NoSQL functions. Data modeling has never been easier and safer thanks to the No Code revolution, so you can simply create your data pipelines with drag-and-drop functions and stop wasting your time by coding what can now be done in minutes! 

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Brian Laleye
Brian Laleye
Brian is the co-founder of RestApp. He is a technology evangelist and passionate about innovation. He has an extensive experience focusing on modern data stack.

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