Software Alternatives, Accelerators & Startups

DrawSQL VS Keras

Compare DrawSQL VS Keras and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

DrawSQL logo DrawSQL

Easy database diagrams. Create, visualize and collaborate on your database entity relationship diagrams.

Keras logo Keras

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
  • DrawSQL Landing page
    Landing page //
    2022-10-03

DrawSQL is a simple, beautiful database diagram editor for developers to ๐Ÿšง create, ๐Ÿ’ฌ collaborate and ๐Ÿ‘€ visualize their entity relationship diagrams.

  • Keras Landing page
    Landing page //
    2023-10-16

DrawSQL

$ Details
freemium $15.0 / Monthly
Platforms
Browser
Release Date
2018 November

Keras

Website
keras.io
Pricing URL
-
$ Details
Platforms
-
Release Date
-

DrawSQL features and specs

  • Easy to Set-up and use
  • Clean UI
  • Free Trial

Keras features and specs

  • User-Friendly
    Keras provides a simple and intuitive interface, making it easy for beginners to start building and training models without needing extensive experience in deep learning.
  • Modularity
    Keras follows a modular design, allowing users to easily plug in different neural network components, such as layers, activation functions, and optimizers, to create complex models.
  • Pre-trained Models
    Keras includes a wide range of pre-trained models and offers easy integration with transfer learning techniques, reducing the time required to achieve good results on new tasks.
  • Integration with TensorFlow
    As part of TensorFlowโ€™s ecosystem, Keras provides deep integration with TensorFlow functionalities, enabling users to leverage TensorFlow's powerful features and performance optimizations.
  • Extensive Documentation
    Keras has comprehensive and well-organized documentation, along with numerous tutorials and code examples, making it easier for developers to learn and use the framework.
  • Community Support
    Keras benefits from a large and active community, which provides support through forums, GitHub, and specialized user groups, facilitating the resolution of issues and sharing of best practices.

Possible disadvantages of Keras

  • Performance Limitations
    Due to its high-level abstraction, Keras may incur performance overheads, making it less suitable for scenarios requiring extremely fast execution and low-level optimizations.
  • Limited Low-Level Control
    The simplicity and abstraction of Keras can be a downside for advanced users who need fine-grained control over model components and custom operations, which may require them to resort to lower-level frameworks.
  • Scalability Issues
    In some complex applications and large-scale deployments, Keras might face scalability challenges, where more specialized or low-level frameworks could handle such tasks more efficiently.
  • Dependency on TensorFlow
    While the integration with TensorFlow is generally an advantage, it also means that the performance and features of Keras are closely tied to the development and updates of TensorFlow.
  • Lagging Behind Latest Research
    Keras, being a user-friendly high-level API, might not always incorporate the latest cutting-edge research advancements in deep learning as quickly as more research-oriented frameworks.

Analysis of Keras

Overall verdict

  • Keras is a solid choice for deep learning projects, offering simplicity and flexibility without sacrificing performance. It is well-suited for educational purposes, research, and even deploying models in production environments.

Why this product is good

  • Keras is widely regarded as a good deep learning library because it provides a user-friendly API that allows for easy and fast prototyping of neural networks. It is built on top of other libraries like TensorFlow, making it robust and efficient for both beginners and experienced developers. Its modularity, extensibility, and compatibility with other tools and libraries make it a popular choice for developing deep learning models.

Recommended for

  • Beginners who are new to deep learning
  • Researchers looking for an easy-to-use platform for prototyping models
  • Developers working on projects that require quick experimentation and development
  • Individuals and companies deploying models into production environments

DrawSQL videos

DrawSQL: Create and visualize beautiful database entity relationship diagrams.

Keras videos

3. Deep Learning Tutorial (Tensorflow2.0, Keras & Python) - Movie Review Classification

More videos:

  • Review - Movie Review Classifier in Keras | Deep Learning | Binary Classifier
  • Review - EKOR KERAS!! Review and Bike Check DARTMOOR HORNET 2018 // MTB Indonesia

Category Popularity

0-100% (relative to DrawSQL and Keras)
Database Tools
100 100%
0% 0
Data Science And Machine Learning
SQL Diagrams
100 100%
0% 0
OCR
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare DrawSQL and Keras

DrawSQL Reviews

Best Database Diagram Tools โ€“ Free and Paid
Web tools like dbdiagram.io, DrawSQL, and SqlDBM are ideal for remote teams, quick access, and easy sharing. They run in the browser, require no setup, and often include real-time collaboration. Desktop tools like dbForge Studio and DbSchema, on the other hand, offer deeper control, live database integration, and richer offline capabilitiesโ€”ideal for complex enterprise...
Source: blog.devart.com
8 Best Database Design Tools in 2025
DrawSQL is a fast and user-friendly tool designed for creating, visualizing, and designing ER diagrams. It enables users to analyze relationships among database objects and generate SQL (DDL) scripts to convert diagrams into databases. Additionally, users can export live documents of their database schemas for future reference. DrawSQL suits both individual users and...
Source: www.devart.com

Keras Reviews

10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by Franรงois Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
15 data science tools to consider using in 2021
Keras is a programming interface that enables data scientists to more easily access and use the TensorFlow machine learning platform. It's an open source deep learning API and framework written in Python that runs on top of TensorFlow and is now integrated into that platform. Keras previously supported multiple back ends but was tied exclusively to TensorFlow starting with...

Social recommendations and mentions

Based on our record, Keras should be more popular than DrawSQL. It has been mentiond 35 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

DrawSQL mentions (12)

  • AI assistance in Development
    With this, I went for designing the db. I went to http://drawsql.app/ and created my first draft. Then exported the DDL and did a bit of back and forth with AI. This is the final draft of the database:. - Source: dev.to / 8 months ago
  • How Changing Requirements Shape the Infrastructure of a Software Project
    So I started designing the DB using this cool tool. The project has 2 tables, users and categories . The user can create many categories as he wants so the first approach I took was creating a third table, a union table to store user_id and category_id. With this solution the users are able to create x numbers of categories and we can see assign the category to the user. - Source: dev.to / over 1 year ago
  • Creating Diagrams and Databases with Online Tools
    Once you have generated the SQL code, you can convert it into a relational schema (the graphical table model) using DrawSQL. This tool offers:. - Source: dev.to / over 1 year ago
  • ๐Ÿ–Œ๏ธ 5+1 Online Tools for Sketches, Wireframes, Drawings, and Diagrams
    DrawSQL makes it easy for teams to collaborate on creating and maintaining schema diagrams. With a single source of truth, there's no need for manually syncing diagram files between different developers and offline tools anymore. Source: about 3 years ago
  • Newbie: Trying to use Supabase Auth fully with its database.
    To be honest, since you are just getting started, I think you should reconsider simplifying this app to begin with. Built something easier and get some more experience before jumping in the ocean. Maybe start by focusing only on the parent company and sub-companies. However, I strongly recommend you to try and make a diagram of your database with relations and columns as it can you a lot of time. I personally use... Source: about 3 years ago
View more

Keras mentions (35)

  • Top Programming Languages for AI Development in 2025
    The unchallenged leader in AI development is still Python. And Keras, and robust community support. - Source: dev.to / about 1 year ago
  • Top 8 OpenSource Tools for AI Startups
    If you need simplicity, Keras is a great high-level API built on top of TensorFlow. It lets you quickly prototype neural networks without worrying about low-level implementations. Keras is perfect for getting those first models up and runningโ€”an essential part of the startup hustle. - Source: dev.to / over 1 year ago
  • Top 5 Production-Ready Open Source AI Libraries for Engineering Teams
    At its heart is TensorFlow Core, which provides low-level APIs for building custom models and performing computations using tensors (multi-dimensional arrays). It has a high-level API, Keras, which simplifies the process of building machine learning models. It also has a large community, where you can share ideas, contribute, and get help if you are stuck. - Source: dev.to / almost 2 years ago
  • Using Google Magika to build an AI-powered file type detector
    The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / about 2 years ago
  • My Favorite DevTools to Build AI/ML Applications!
    As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 2 years ago
View more

What are some alternatives?

When comparing DrawSQL and Keras, you can also consider the following products

DBDiagram.io - Free database diagrams designer for analysts & developers ๐Ÿ› 

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Azimutt - Next-Gen ERD to Design, Explore and Document real world databases (big and messy ones ^^)

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

MySQL Workbench - MySQL Workbench is a unified visual tool for database architects, developers, and DBAs.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.