Software Alternatives, Accelerators & Startups

Dataiku VS Hibernate

Compare Dataiku VS Hibernate 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.

Dataiku logo Dataiku

Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.

Hibernate logo Hibernate

Hibernate an open source Java persistence framework project.
  • Dataiku Landing page
    Landing page //
    2023-08-17
  • Hibernate Landing page
    Landing page //
    2022-04-25

Dataiku

$ Details
-
Release Date
2013 January
Startup details
Country
United States
State
New York
City
New York
Founder(s)
Clément Stenac
Employees
500 - 999

Dataiku features and specs

  • User-Friendly Interface
    Dataiku offers an intuitive and easy-to-navigate visual interface that allows users of all technical backgrounds to create, manage, and deploy data projects without needing extensive coding knowledge.
  • Collaborative Environment
    The platform supports collaborative work, enabling data scientists, engineers, and analysts to work together on the same projects seamlessly, sharing insights and models easily.
  • End-to-End Workflow
    Dataiku provides tools that cover the entire data pipeline, from data preparation and cleaning to model building, deployment, and monitoring, making it a comprehensive solution for data teams.
  • Integrations and Extensibility
    The platform integrates with many data storage systems, machine learning libraries, and cloud services, allowing users to leverage existing tools and infrastructure.
  • Automation Capabilities
    Dataiku offers automation features such as scheduling, automation scenarios, and machine learning model monitoring, which can significantly enhance productivity and efficiency.
  • Rich Documentation and Support
    Dataiku provides extensive documentation, tutorials, and a strong support community to help users navigate the platform and troubleshoot issues.

Possible disadvantages of Dataiku

  • Pricing
    Dataiku can be expensive, particularly for small businesses and startups. The cost may be a barrier to entry for organizations with limited budgets.
  • Resource Intensive
    The platform can be resource-hungry, requiring significant computing power, which may necessitate additional investments in hardware or cloud services.
  • Learning Curve for Advanced Features
    Although the basic interface is user-friendly, mastering advanced features and customizations can require a steep learning curve and significant training.
  • Limited Offline Capabilities
    Dataiku relies heavily on cloud services for many of its functionalities. This dependence might be restrictive in environments with limited or no internet access.
  • Custom Model Flexibility
    While Dataiku supports many machine learning frameworks, the process of integrating custom or niche models can be cumbersome compared to using those frameworks directly.
  • Dependency on Ecosystem
    The seamless experience of Dataiku often relies on the broader cloud and data ecosystem. Changes or issues in integrated services can impact its performance and reliability.

Hibernate features and specs

  • Object-Relational Mapping
    Hibernate simplifies database interaction in Java by providing Object-Relational Mapping (ORM), allowing developers to map Java objects to database tables without writing repetitive SQL code.
  • Automatic Table Generation
    Hibernate can automatically generate database tables based on your Java entity classes, reducing the need for manually creating and maintaining database schemas.
  • HQL (Hibernate Query Language)
    Hibernate provides its own query language, HQL, which allows developers to write queries in an object-oriented manner and reduces the dependency on SQL.
  • Caching
    Hibernate supports caching mechanisms like first-level cache (session cache) and second-level cache, which can significantly improve performance by reducing the number of database hits.
  • Transaction Management
    Hibernate integrates with the Java Transaction API (JTA) to provide robust transaction management, ensuring data consistency and reducing the complexities of handling transactions manually.
  • Lazy Loading
    Hibernate supports lazy loading of associated entities, which can optimize performance by retrieving only the necessary data from the database on-demand.

Possible disadvantages of Hibernate

  • Learning Curve
    Hibernate has a steep learning curve for beginners due to its extensive set of features and configurations, which can be overwhelming initially.
  • Performance Overhead
    The abstraction layer provided by Hibernate can introduce a performance overhead compared to using plain SQL queries, especially in complex queries or large-scale applications.
  • Complexity in Configuration
    While Hibernate provides flexibility in configuration, it can become complex and cumbersome to manage, especially in large applications or when tuning performance.
  • Debugging Difficulty
    Debugging issues in Hibernate can be challenging due to its abstraction and proxy mechanisms, making it harder to trace problems back to the source.
  • Dependency Management
    The use of Hibernate adds additional dependencies to your project, which can complicate dependency management and increase the size of your application.
  • Limited Control Over SQL
    Hibernate abstracts away SQL, which can be a disadvantage for developers who need fine-grained control over the generated SQL and database optimizations.

Dataiku videos

AutoML with Dataiku: And End-to-End Demo

More videos:

  • Review - Dataiku: For Everyone in the Data-Powered Organization
  • Tutorial - Dataiku DSS Tutorial 101: Your very first steps

Hibernate videos

Should you Hibernate, Shut down, or put your PC to sleep?

More videos:

  • Review - GELERT Hibernate 400 sleeping bag review.
  • Tutorial - Java Hibernate Tutorial Part 8 Chapter 1 Review 1

Category Popularity

0-100% (relative to Dataiku and Hibernate)
Data Science And Machine Learning
Web Frameworks
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Developer Tools
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 Dataiku and Hibernate

Dataiku Reviews

15 data science tools to consider using in 2021
Some platforms are also available in free open source or community editions -- examples include Dataiku and H2O. Knime combines an open source analytics platform with a commercial Knime Server software package that supports team-based collaboration and workflow automation, deployment and management.
The 16 Best Data Science and Machine Learning Platforms for 2021
Description: Dataiku offers an advanced analytics solution that allows organizations to create their own data tools. The company’s flagship product features a team-based user interface for both data analysts and data scientists. Dataiku’s unified framework for development and deployment provides immediate access to all the features needed to design data tools from scratch....

Hibernate Reviews

17 Popular Java Frameworks for 2023: Pros, cons, and more
MyBatis is somewhat similar to the Hibernate framework, as both facilitate communication between the application layer and the database. However, MyBatis doesn’t map Java objects to database tables like Hibernate does — instead, it links Java methods to SQL statements. As a result, SQL is visible when you’re working with the MyBatis framework, and you still have control over...
Source: raygun.com
10 Best Java Frameworks You Should Know
Hibernate is one of the best Frameworks which is capable of extending Java's Persistence API support. Hibernate is an open-source, extremely lightweight, performance-oriented, and ORM (Object-Relational-Mapping) tool.

Social recommendations and mentions

Based on our record, Hibernate seems to be more popular. It has been mentiond 16 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.

Dataiku mentions (0)

We have not tracked any mentions of Dataiku yet. Tracking of Dataiku recommendations started around Mar 2021.

Hibernate mentions (16)

  • How To Secure APIs from SQL Injection Vulnerabilities
    Object-Relational Mapping frameworks like Hibernate (Java), SQLAlchemy (Python), and Sequelize (Node.js) typically use parameterized queries by default and abstract direct SQL interaction. These frameworks help eliminate common developer errors that might otherwise introduce vulnerabilities. - Source: dev.to / 3 months ago
  • Top 10 Java Frameworks Every Dev Need to Know
    Overview: Hibernate is a Java ORM (Object Relational Mapping) framework that simplifies database operations by mapping Java objects to database tables. It allows developers to focus on business logic without worrying about SQL queries, making database interactions seamless and more maintainable. - Source: dev.to / 6 months ago
  • In One Minute : Hibernate
    Hibernate is the umbrella for a collection of libraries, most notably Hibernate ORM which provides Object/Relational Mapping for java domain objects. In addition to its own "native" API, Hibernate ORM is also an implementation of the Java Persistence API (jpa) specification. - Source: dev.to / over 2 years ago
  • Spring Boot – Black Box Testing
    I'm using Spring Data JPA as a persistence framework. Therefore, those classes are Hibernate entities. - Source: dev.to / over 2 years ago
  • How to Secure Nodejs Application.
    To prevent SQL Injection attacks to sanitize input data. You can either validate every single input or validate using parameter binding. Parameter binding is mostly used by developers as it offers efficiency and security. If you are using a popular ORM such as sequelize, hibernate, etc then they already provide the functions to validate and sanitize your data. If you are using database modules other than ORM such... - Source: dev.to / almost 3 years ago
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What are some alternatives?

When comparing Dataiku and Hibernate, you can also consider the following products

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

Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Grails - An Open Source, full stack, web application framework for the JVM

NumPy - NumPy is the fundamental package for scientific computing with Python

Sequelize - Provides access to a MySQL database by mapping database entries to objects and vice-versa.