Software Alternatives, Accelerators & Startups
Register | Login

Hadoop VS DreamFactory

Compare Hadoop VS DreamFactory and see what are their differences

Cyclr
Powerful SaaS integration toolkit for SaaS developers - create, amplify, manage and publish native integrations from within your app with Cyclr's flexible Embedded iPaaS. featured
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.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing

DreamFactory logo DreamFactory

DreamFactory is an API management platform used to generate, secure, document, and extend APIs.
  • Hadoop Landing page
    Landing page //
    2021-09-17
  • DreamFactory Landing page
    Landing page //
    2024-10-01

DreamFactory is an API management platform used to generate, secure, document, and extend APIs. The platform is used within a wide variety of sectors, including banking, auto manufacturing, online gaming, consulting, and government.

Perhaps best known for its API generation capabilities, the platform can generate APIs for 20 databases including MySQL, Microsoft SQL Server, Oracle, and MongoDB, among others. Generators are also available for Excel, AWS S3, email delivery providers, and IoT.

Authentication and security is another core feature. APIs can be authenticated using API keys, Active Directory, LDAP, OAuth, OpenID Connect, SAML 2.0, and Okta. A robust yet convenient set of role-based access controls (RBACs) allow administrators to easily create highly tailored API access rules.

DreamFactory's scripting engine supports PHP, Python (version 2 and 3) and NodeJS. Developers can use the engine to create entirely scripted APIs which incorporate third-party libraries and packages. The scripting engine can also be used to extend existing endpoints, allowing developers to implement API composition, apply data masking and hiding, response transformation, and more.

Recently added features include restricted administrators, API scheduling, API auditing, and API generation connectors for Snowflake, Hadoop, and Apache Hive.

Hadoop features and specs

  • Scalability
    Hadoop can easily scale from a single server to thousands of machines, each offering local computation and storage.
  • Cost-Effective
    It utilizes a distributed infrastructure, allowing you to use low-cost commodity hardware to store and process large datasets.
  • Fault Tolerance
    Hadoop automatically maintains multiple copies of all data and can automatically recover data on failure of nodes, ensuring high availability.
  • Flexibility
    It can process a wide variety of structured and unstructured data, including logs, images, audio, video, and more.
  • Parallel Processing
    Hadoop's MapReduce framework enables the parallel processing of large datasets across a distributed cluster.
  • Community Support
    As an Apache project, Hadoop has robust community support and a vast ecosystem of related tools and extensions.

Possible disadvantages of Hadoop

  • Complexity
    Setting up, maintaining, and tuning a Hadoop cluster can be complex and often requires specialized knowledge.
  • Overhead
    The MapReduce model can introduce additional overhead, particularly for tasks that require low-latency processing.
  • Security
    While improvements have been made, Hadoop's security model is considered less mature compared to some other data processing systems.
  • Hardware Requirements
    Though it can run on commodity hardware, Hadoop can still require significant computational and storage resources for larger datasets.
  • Lack of Real-Time Processing
    Hadoop is mainly designed for batch processing and is not well-suited for real-time data analytics, which can be a limitation for certain applications.
  • Data Integrity
    Distributed systems face challenges in maintaining data integrity and consistency, and Hadoop is no exception.

DreamFactory features and specs

  • Ease of Use
    DreamFactory offers a user-friendly interface that makes it easy to create, manage, and deploy APIs without extensive coding skills.
  • Automatic API Generation
    Generates REST APIs for various data sources automatically, saving development time and reducing potential errors.
  • Wide Database Support
    Supports numerous databases and storage engines, including SQL, NoSQL, and file storage systems, providing great flexibility.
  • Scalability
    Can handle enterprise-level projects, ensuring that APIs can scale easily with growing business needs.
  • Security Features
    Includes robust security features like role-based access, OAuth, Single Sign-On (SSO), and API key management.
  • Cross-Platform
    Works on multiple platforms including Linux, Windows, and Mac, making it versatile for different development environments.
  • Integrations
    Supports integration with numerous third-party services and software, facilitating seamless business operations.
  • Open Source Option
    Offers an open-source version, providing more flexibility and cost savings for developers and organizations.

Possible disadvantages of DreamFactory

  • Learning Curve
    Even though it's user-friendly, there is still a learning curve involved, especially for beginners not familiar with API management.
  • Pricing
    While an open-source version is available, advanced features and enterprise-level support require a paid subscription, which can be costly.
  • Performance Overhead
    In some cases, the additional layers of abstraction can add overhead, potentially affecting performance.
  • Complexity in Advanced Use Cases
    For highly complex or custom scenarios, limitations may arise, requiring additional custom development.
  • Limited Extensions
    Compared to some competitors, the ecosystem of plugins and extensions may be less extensive.
  • Community Support
    The open-source community around DreamFactory is not as large as some other projects, which may limit peer support and available resources.
  • Concurrency Handling
    May require additional configuration or optimization to handle high concurrency situations effectively.

Analysis of Hadoop

Overall verdict

  • Hadoop is a robust and powerful data processing platform that is well-suited for organizations that need to manage and analyze large-scale data. Its resilience, scalability, and open-source nature make it a popular choice for big data solutions. However, it may not be the best fit for all use cases, especially those requiring real-time processing or where ease of use is a priority.

Why this product is good

  • Hadoop is renowned for its ability to store and process large datasets using a distributed computing model. It is scalable, cost-effective, and efficient in handling massive volumes of data across clusters of computers. Its ecosystem includes a wide range of tools and technologies like HDFS, MapReduce, YARN, and Hive that enhance data processing and analysis capabilities.

Recommended for

  • Organizations dealing with vast amounts of data needing efficient batch processing.
  • Businesses that require scalable storage solutions to manage their data growth.
  • Companies interested in leveraging a diverse ecosystem of data processing tools and technologies.
  • Technical teams that have the expertise to manage and optimize complex distributed systems.

Analysis of DreamFactory

Overall verdict

  • Overall, DreamFactory is a solid choice for developers and organizations looking for a comprehensive and efficient way to manage API generation and backend development. Its ease of use, wide range of features, and support for numerous data sources make it highly recommended for those seeking to simplify their development workflow.

Why this product is good

  • DreamFactory is considered a good option for creating robust and scalable REST APIs because it automates a lot of backend processes, allowing developers to focus on their core application logic. It offers features like API management, user authentication, role-based access control, and data integration with various databases and cloud services, which streamline the development process. Additionally, DreamFactory supports multiple scripting languages, providing flexibility and customization options that suit different use cases.

Recommended for

    DreamFactory is particularly recommended for developers who need to quickly generate APIs without spending extensive time managing backend infrastructure. It is suitable for small to medium-sized enterprises, independent developers, and teams that require rapid prototyping and development. Organizations looking for a solution to manage multiple data resources and integrate various third-party services can also greatly benefit from DreamFactory's capabilities.

Hadoop videos

+ Add

What is Big Data and Hadoop?

More videos:

  • Review - Product Ratings on Customer Reviews Using HADOOP.
  • Tutorial - Hadoop Tutorial For Beginners | Hadoop Ecosystem Explained in 20 min! - Frank Kane

DreamFactory videos

No DreamFactory videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Hadoop and DreamFactory)

Hadoop

DreamFactory

Databases
100 100%
Databases
0% 0
API Tools
0 0%
API Tools
100% 100
Big Data
100 100%
Big Data
0% 0
APIs
0 0%
APIs
100% 100

User comments

Share your experience with using Hadoop and DreamFactory. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

Hadoop Reviews

A List of The 16 Best ETL Tools And Why To Choose Them
Companies considering Hadoop should be aware of its costs. A significant portion of the cost of implementing Hadoop comes from the computing power required for processing and the expertise needed to maintain Hadoop ETL, rather than the tools or storage themselves.
Source: www.datacamp.com
16 Top Big Data Analytics Tools You Should Know About
Hadoop is an Apache open-source framework. Written in Java, Hadoop is an ecosystem of components that are primarily used to store, process, and analyze big data. The USP of Hadoop is it enables multiple types of analytic workloads to run on the same data, at the same time, and on a massive scale on industry-standard hardware.
Source: www.analytixlabs.co.in
5 Best-Performing Tools that Build Real-Time Data Pipeline
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than relying on hardware to deliver high-availability, the library itself is...
Source: www.analyticsinsight.net

DreamFactory Reviews

7 Best NoSQL APIs
DreamFactory is a great choice for developers or businesses who want to create a quick API to work with a NoSQL database. The process couldn’t be easier. Developers only need to provide the database information, and DreamFactory automatically creates a full-fledged REST API or a SOAP API.
Source: www.programmableweb.com

Social recommendations and mentions

Based on our record, Hadoop seems to be a lot more popular than DreamFactory. While we know about 25 links to Hadoop, we've tracked only 1 mention of DreamFactory. 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.

Hadoop mentions (25)

  • Apache Hadoop: Open Source Business Model, Funding, and Community
    This post provides an in‐depth look at Apache Hadoop, a transformative distributed computing framework built on an open source business model. We explore its history, innovative open funding strategies, the influence of the Apache License 2.0, and the vibrant community that drives its continuous evolution. Additionally, we examine practical use cases, upcoming challenges in scaling big data processing, and future... - Source: dev.to / 26 days ago
  • What is Apache Kafka? The Open Source Business Model, Funding, and Community
    Modular Integration: Thanks to its modular approach, Kafka integrates seamlessly with other systems including container orchestration platforms like Kubernetes and third-party tools such as Apache Hadoop. - Source: dev.to / 26 days ago
  • India Open Source Development: Harnessing Collaborative Innovation for Global Impact
    Over the years, Indian developers have played increasingly vital roles in many international projects. From contributions to frameworks such as Kubernetes and Apache Hadoop to the emergence of homegrown platforms like OpenStack India, India has steadily carved out a global reputation as a powerhouse of open source talent. - Source: dev.to / about 1 month ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 3 months ago
  • Apache Hadoop: Pioneering Open Source Innovation in Big Data
    Apache Hadoop is more than just software—it’s a full-fledged ecosystem built on the principles of open collaboration and decentralized governance. Born out of a need to process vast amounts of information efficiently, Hadoop uses a distributed file system and the MapReduce programming model to enable scalable, fault-tolerant computing. Central to its success is a diverse ecosystem that includes influential... - Source: dev.to / 3 months ago
View more

DreamFactory mentions (1)

What are some alternatives?

When comparing Hadoop and DreamFactory, you can also consider the following products

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Postman - The Collaboration Platform for API Development

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

MuleSoft Anypoint Platform - Anypoint Platform is a unified, highly productive, hybrid integration platform that creates an application network of apps, data and devices with API-led connectivity.

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.

AWS CloudTrail - AWS CloudTrail is a web service that records AWS API calls for your account and delivers log files to you.

Loading...