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MySQL VS Keras

Compare MySQL VS Keras and see what are their differences

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  4. » Alternatives

MySQL logo MySQL

The world's most popular open source database

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.
  • MySQL Landing page
    Landing page //
    2022-06-17
  • Keras Landing page
    Landing page //
    2023-10-16

MySQL features and specs

  • Reliability
    MySQL is known for its reliability and durability, making it a solid choice for many businesses' database management needs.
  • Performance
    It offers robust performance, handling large databases and complex queries efficiently.
  • Open Source
    MySQL is an open-source database, making it freely available under the GNU General Public License (GPL).
  • Scalability
    MySQL supports large-scale applications and can handle high volumes of transactions.
  • Community Support
    There is a large, active MySQL community that offers extensive resources, documentation, and support.
  • Cross-Platform
    MySQL is compatible with various operating systems like Windows, Linux, and macOS.
  • Integrations
    MySQL integrates well with numerous development frameworks, including LAMP (Linux, Apache, MySQL, PHP/Python/Perl).
  • Security
    MySQL offers various security features, such as user account management, password policies, and encrypted connections.
  • Cost
    The open-source nature of MySQL means that it can be very cost-effective, especially for small to medium-sized businesses.

Possible disadvantages of MySQL

  • Support
    While community support is plentiful, official support from Oracle can be quite expensive.
  • Complexity
    More advanced features and configurations can be complex and may require a steep learning curve for new users.
  • Scalability Limitations
    While MySQL is scalable, very high-scale applications may run into limitations compared to some newer database technologies.
  • Plug-in Storage Engines
    The use of plug-in storage engines like InnoDB or MyISAM can cause inconsistencies and complicate backups and recovery processes.
  • ACID Compliance
    Although MySQL supports ACID compliance, certain configurations or storage engines may not fully adhere to ACID properties, affecting transaction reliability.
  • Concurrent Writes
    Handling a high number of concurrent writes can be less efficient compared to some other database systems designed specifically for high concurrency.
  • Feature Set
    Some advanced features found in other SQL databases (e.g., full-text indexing, rich analytics) may be less robust or absent.
  • Vendor Dependency
    With Oracle now owning MySQL, there can be concerns about licensing changes or other forms of vendor lock-in.
  • Replication Complexities
    Setting up replication and ensuring data consistency across distributed systems can be complex and error-prone.

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 TensorFlow’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.

MySQL videos

+ Add

MySQL IN 10 MINUTES (2020) | Introduction to Databases, SQL, & MySQL

More videos:

  • Review - A Review of MySQL Open Source Software

Keras videos

+ Add

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 MySQL and Keras)

MySQL

Keras

Databases
100 100%
Databases
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Relational Databases
100 100%
Relational Databases
0% 0
Data Science Tools
0 0%
Data Science Tools
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 MySQL and Keras

MySQL Reviews

MariaDB Vs MySQL In 2019: Compatibility, Performance, And Syntax
MySQL: MySQL is an open-source relational database management system (RDBMS). Just like all other relational databases, MySQL uses tables, constraints, triggers, roles, stored procedures and views as the core components that you work with. A table consists of rows, and each row contains a same set of columns. MySQL uses primary keys to uniquely identify each row (a.k.a...
Source: blog.panoply.io
20+ MongoDB Alternatives You Should Know About
MySQL® is another feasible replacement. MySQL 5.7 and MySQL 8 have great support for JSON, and it continues to get better with every maintenance release. You can also consider MySQL Cluster for medium size sharded environments. You can also consider MariaDB and Percona Server for MySQL
Source: www.percona.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 François 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...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Keras should be more popular than MySQL. 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.

MySQL mentions (4)

  • I have a recurring issue with a MySQL DB where I continually run out of disk space due to logs being filled. I've tried everything I can think of. Can anyone think of anything else I should try?
    So, I did a quick read through the mysql reference and found a bunch of flush related commands. I tried:. Source: almost 2 years ago
  • MMORPG design resources
    MySQL: Any SQL or DB knock-off, really... mysql.com - mariadb.org - sqlite.org. Source: over 2 years ago
  • Probably a syntax error
    15 years and five strokes ago. I was a Unix sysadmin. ALthough I was never an actual programmer, I did maintenance/light enhancement for the organization's website, in php. Now, as self-administered cognative therapy, I'm going back to it. This is an evil HR application that uses the mysql.com employees sample database. The module below enables the evil HR end user to generate a list of the oldest workers so... Source: almost 4 years ago
  • An absolute nightmare with mysql 8.0.25
    I always use the packages from mysql.com, that way I don't have to deal with strange configuration stuff along those lines, but anyway, I'm afraid I'm out of ideas. Surely someone else would have run in to the same issue here though. Source: almost 4 years ago

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 / 13 days 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 running—an essential part of the startup hustle. - Source: dev.to / 7 months 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 / 7 months 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 / 11 months 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 1 year ago
View more

What are some alternatives?

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

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

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.

Microsoft SQL - Microsoft SQL is a best in class relational database management software that facilitates the database server to provide you a primary function to store and retrieve data.

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

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

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

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