Top 10 Powerful Data Modeling Tools to Know in 2022

on Data Driven, Data Modelling, Tutorials • December 14th, 2021 • Write for Hevo

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Data Modeling is a subject you may already be familiar with if your company interacts with Big Data in any way. You can use Data Modeling Tools to construct new databases or to create an overall IT strategy for your company.

Data might be regarded to be an ace card for firms in the technology era. Dealing with a huge number of data aspects might be quite challenging. This is when Data Modeling comes into the picture. Data Modeling Tools allow you to show how Data Structures that support business operations will be constructed, how data will be arranged, and what links we want to make between them.

This article provides a holistic view of Data Modeling and Data Modeling Tools. You will understand the need for Data Modeling Tools and explore their key benefits. You will also understand the significant data models used in Data Modeling. In addition, you will learn some of the critical factors to keep in mind while selecting the right Data Modeling Tool for your use case. At the end of this article, you will unravel the popular Data Modeling Tools available in the market.

Table of Contents

Introduction to Data Modeling

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The practice of examining data objects and their relationships with other objects is known as Data Modeling. It’s utilized to look into the data requirements for various business activities. The data models are constructed to store the information in a database. The purpose is to show the many types of data that are needed and stored in the system, as well as the links between them, how the data can be categorized and arranged, and its formats and features. Data Models are created throughout the project’s design and analysis phase to verify that the application’s requirements are met. 

In the 1990s and early 2000s, software programmers established a data model for the whole database before beginning to code. Today under Agile and DevOps, you subdivide the entire database into functional sections or sub-models to create progressively inside the overall application’s SCRUM (Systematic Customer Resolution Unraveling Meeting) sprints. As a result, database design benefits from the classic “divide and conquer” strategy, which is matched to the application phase. The generated databases will now fulfill the business’s effectiveness and efficiency needs. 

Understanding Data Modeling Tools

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Data Modeling Tools make it possible to model data quickly and efficiently. They provide a link between the data and the various levels of data models. Most Data Modeling Tools will automatically build database schemas, allow for schema and model merger and comparison, and reverse engineer existing databases into models. Today, a variety of commercial and free source Computer-Aided Software Engineering (CASE) solutions, including Data Modeling, Diagramming, and Visualization tools, are widely used.

Data Modeling Tools make database design rapid and easy while reducing human mistakes. It aids in the development of a high-performance database, the generation of meaningful reports for stakeholders, and the creation of Data Definition Language (DDL). A well-designed database reduces the likelihood of failure, reduces maintenance work, and shortens the time it takes to execute a task.

Understanding the Need for Data Modeling Tools

Data is the most valuable asset for most businesses. As a result, the Database you employ to store this asset is more crucial than ever. When you consider that Data Analytics and Data Scientists want to be able to slice and dice the data to support major strategic business decisions, having the data in a design that supports the application that puts it in motion, as well as providing useful content while the data is at rest, is critical. You must now plan for both sorts of requirements.

Simply defined, whatever data you have must be converted into a specific format to be stored in a database (i.e. data model needs to be created). As a result, Data Modeling Tools will allow you to construct these diagrams and models. When a data model is applied in a system, it strengthens and enforces the business principles that it represents. Describing the objects and actions in an organization is similar to defining the entities and relationships in a data model.

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Types of Data Models

Data Modeling strategies must be aligned with database design schemas since they are implemented within companies based on business needs. In any software development or maintenance project, Data Modeling is a crucial and necessary stage. It’s advisable to start with high-level business needs and work your way down to a granular database or file structure when creating a data model. The following three types of data models are used in this method:

1) Conceptual Data Model

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The first sketches of the tables that would make up the full database system are created in this section of the process. The UML language is used to carry out this design, with use-case diagrams visually detailing the tasks that must be completed and the players engaged in each of them. Instead of focusing on processing flow, this sort of Data Modelling focuses on locating the data employed in a business. This data model’s primary goal is to organize and establish business rules and ideas.

2) Logical Data Model

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This model takes into consideration the rules and some specified resource limits when aggregating implementation details. It is possible to define attributes here that will constitute the structure’s key. Companies that are significantly involved in Data Warehousing frequently use this technique. For Data Analytics, logical data models assist enterprises in formulating data consolidation and segregation. The Logical Model is created by Data Architects. It can be used to convert it to a database. The root package object always has this sort of Data Modelling.

3) Physical Data Model

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The physical data model displays the data while taking into consideration all of the database’s rules and restrictions. Companies use physical data models to finalize table relationships and deploy the appropriate databases. The Database Administrator (DBA) and Developers design this model. This form of Data Modelling aids in the creation of the schema by abstracting the databases. It also specifies the data model’s specific implementation.

Critical Factors to Consider while Selecting the Data Modeling Tools

It might be difficult to find the correct tool or application for you when the complexity of Data Modeling Tools available increases. As a result, it’s critical to assess your use case based on a few key factors:

  • Usage and Needs: This is the most important consideration when selecting a Data Modeling Tool. Each Data Modeling Tool focuses on a different aspect of Data Modeling. To make the best decision, you should first write out your business needs. A project that needs a Data Modeling Tool for modest tasks, for example, would benefit greatly from one that has modeling capabilities built into the database. However, when Data Modeling needs to respond to corporate demands, the same technology will not work.
  • Scalability: A project’s needs change as it progresses. Make sure you use a tool that allows you to expand. Before choosing a Data Modeling Tool, consider the use case and size of the data model. It is critical to consider the current requirements while choosing a tool.
  • Features: After you’ve figured out what the business needs are, you’ll need to compare and contrast various Data Modeling Tools. This entails determining if the Data Modeling Tools can conduct UTM or use case modeling, as well as whether they can handle multiple users. Also, whether or not it supports conceptual, logical, and physical Data Modeling. Make a list of features and compare them.
  • Integration: Be careful that some Data Modeling Tools use a proprietary format while others utilize a generic format to construct a data model. Select your modeling tool carefully to ensure that the final output fits seamlessly into the database or existing tech setup/workflows.
  • User Community: Every tool has a user community where you can ask questions and get answers. Make sure your tool isn’t isolated and has large community support.

Best Data Modeling Tools in the Market

For various database platforms, a large number of Data Modeling Tools are available. Selecting one that meets the user’s needs is quite challenging. Explore the most popular Data Modeling Tools below to make this time-consuming work easier.

1) ER/Studio

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Idera’s ER/Studio is a Data Modeling Tool that lets you identify your data assets and sources across several database systems. It can construct and share data models, as well as track them from start to finish. It works on Windows, Linux, and Mac computers. A comprehensive business lexicon can help you define your company terminology, concepts, and relationships. Businesses can quickly model and understand the interaction between processes, data, and people with ER/Studio.

Key Features:

  • It can accommodate both logical and physical designs.
  • For new modifications at the database level, the tool runs an impact analysis.
  • It allows for scripting and automation.
  • HTML, PNG, JPEG, RTF, XML, Schema, and DTD are all supported display formats.
  • It ensures that models and databases are consistent.

Visit ER/Studio page here to know more.

2) DbSchema Pro

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DbSchema Pro is a universal database designer and graphical user interface (GUI) tool for schema documentation and monitoring, as well as sharing and deploying schemas on relational and NoSQL databases.

Key Features:

  • The database is independent of the conceptual and logical designs.
  • You can use Relational Data Explorer to look at and change data from a variety of tables using foreign keys.
  • The Visual Query Builder allows you to create queries with various ordering, grouping, filters and joins.
  • Using reverse regular expressions and specified patterns, the Data Generator can produce test data.
  • Reports and charts can be created using the tool’s configurable designer.

Visit the DbSchema Pro page here to know more.

3) Erwin Data Modeler

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Erwin is a Data Modeling Tool for creating logical, physical, and conceptual data models. It is one of the most effective Data Modeling Tools for creating a database from a physical model. It is renowned for being a low-cost but robust business solution that adheres to governance database principles.

Key Features:

  • It allows business and technical users to collaborate and maintain models from a central location. It also enables you to simulate data from any location.
  • To ensure data quality, the tool employs business data standards.
  • It features a graphical interface that is simple to use.
  • It compares the model and database automatically.
  • Forward and reverse engineering of data definition code can be efficiently synchronized.
  • For effective modeling, it allows you to pull data from CRM, ERP, and other sources.

Visit the Erwin Data Modeler page here to know more.

4) Archi

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Enterprise Architects and Modelers find Archi to be a cost-effective solution. It can be used to analyze, describe, and visualize architecture in a variety of business sectors. It’s a cross-platform, open-source Data Modeling Tool that allows you to scale it with the help of plugins.

Key Features:

  • In ArchiMate views, you can efficiently construct all ArchiMate elements.
  • You can alter the ArchiMate viewpoint at any moment with the tool’s dynamic views.
  • It offers a hints view that allows you to quickly access element information.
  • In a radial-tree visual, this tool shows the selected model element and all of its connections with other model components.
  • You can use the tool to build and customize your canvas.

Visit the Archi page here to know more.

5) SQL Database Modeler

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You can construct a SQL Database online using SQL Database Modeler. You can import and build SQL scripts from it. MS SQL Server and MySQL are supported by it. This tool has a user-friendly interface that makes it easy to create and change tables.  You can collaborate with a group from any location.

Key Features:

  • It allows projects to be converted from MS SQL Server to MySQL and vice versa.
  • It allows users to collaborate on projects. Presentations and documentation can be made with the shared projects.
  • It has a versioning feature. When you save the project, it produces a new version. Any version can be rolled back to, and any version can be seen at any time and from anywhere. These variations can also be labeled.
  • Allows you to share projects and their versions.
  • Various view modes are available.
  • It allows for both forward and reverses engineering.

Visit SQL Database Modeler page here to know more.

6) Oracle SQL Developer Data Modeler

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Oracle SQL Developer Data Modeler is a Data Modeling Tool that enables physical database architecture for the Oracle environment. Capturing, studying, managing, and gaining insights from data are all covered. It is a piece of software that boosts productivity and makes a variety of Data Modeling activities easier.

Key Features:

  • Relational, multi-dimensional, and data type models can all be created and edited.
  • It is capable of both forward and reverse engineering.
  • Through source code management, the tool facilitates collaborative development.
  • It’s one of the greatest free Data Modeling Tools available, and it works in both traditional and cloud settings.

Visit the is Oracle SQL Developer Data Modeler page here to know more.

7) IBM InfoSphere Data Architect

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IBM InfoSphere Data Architect is a Data Modeling Tool for business intelligence and statistics that simplifies and accelerates data integration design. It is one of the most effective Data Modeling Tools for aligning services, applications, data structures, and processes.

Key Features:

  • The tool allows for quick and simple development.
  • It enables you to comprehend data assets to increase productivity and shorten time to market.
  • It facilitates collaboration and integration among teams.
  • Custom mapping can be imported or exported.
  • By examining metadata, the tool automatically determines the structure of disparate data sources.
  • Physical and logical data models can be created.
  • Integration with other products such as data studio and query workload tuner is possible.

Visit the IBM InfoSphere Data Architect page here to know more.

8) MySQL Workbench

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For Data Modeling, SQL development, server configuration, user management, and backup, DBAs, Database Architects, and developers utilize this application. Microsoft Windows, Linux, and Mac are the 3 operating systems supported by the system.

Key Features:

  • Forward and reverse engineering are supported
  • You can use it to construct complicated ER models.
  • You can transfer RDBMS tables, objects, and data from Microsoft SQL Server, Microsoft Access, Sybase ASE, and PostgreSQL to MySQL with this tool.
  • Visual tools can be used to generate, run, and optimize SQL queries.
  • Offers visual tools for setting servers, backup and recovery, user administration, audit data inspection, and database health monitoring.
  • Allows you to view the performance of MySQL applications using the performance dashboard.

Visit the MySQL Workbench page here to know more.

9) Lucidchart

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Lucidchart is a collaborative online tool for creating database diagrams. There’s no need to download bulky software because this Data Modeling solution is cloud-based, and updates are instantaneous. One of the most significant advantages of this tool is that it can save you hours of manual work.

Key Features: 

  • A large number of sophisticated features are available.
  • A plethora of information assets are available and the interface is simple to navigate.
  • It’s a good choice for architectural schematics.
  • The Lucidchart app for Android and iOS is compatible with all three main operating systems and can be used on any mobile device.
  • MySQL, Oracle, SQL Server, and PostgreSQL are among the systems supported.

Visit the is Lucidchart page here to know more.

10) PgModeler

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PgModeler is an open-source Data Modeling Tool for constructing database models that give extensive access to its source code, with a light and appealing interface developed for the PostgreSQL database system.

Key Features:

  • Supports XML files.
  • Columns and restrictions are generated automatically.
  • In the event of a failure, the prior work is restored.
  • To synchronize both the model and the database, you can write SQL scripts.
  • To automate tasks, you can use the command-line interface.
  • Models can be created using data from existing databases.

Visit the PgModeler page here to know more.

Key Benefits of Data Modeling Tools

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Data Modeling Tools can take a complicated software process and turn it into an easy-to-understand visual. Data Modeling Tools has several benefits including the ones mentioned below.

  • Use Data Modeling Tools to organize massive data and make it simpler to find information.
  • Seek visual representations of complex topics to better understand your business.
  • Reduce software and database development pitfalls.
  • Increase enterprise-wide uniformity in documentation and system architecture.
  • Enhance the performance of your application and database.
  • Streamline data mapping across the enterprise.
  • Improve the flow of information between the development and BI teams.
  • At the conceptual, logical, and physical levels, Data Modeling Tools simplify and accelerate the database design process.

Conclusion

In this article, you learned about various aspects of Data Modeling. You explored the key benefits of Data Modeling Tools, learned differences between conceptual, logical, and physical data models. In addition, you also understood the key factors that help in selecting the right Data Modeling Tool. At the end of this article, you unraveled the most powerful Data Modeling Tools in the market. 

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