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Atlassian Fisheye VS Hadoop

Compare Atlassian Fisheye VS Hadoop and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Atlassian Fisheye logo Atlassian Fisheye

With FishEye you can search code, visualize and report on activity and find for commits, files, revisions, or teammates across SVN, Git, Mercurial, CVS and Perforce.

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing
  • Atlassian Fisheye Landing page
    Landing page //
    2023-08-04
  • Hadoop Landing page
    Landing page //
    2021-09-17

Atlassian Fisheye features and specs

  • Code Search
    FishEye provides advanced search capabilities, allowing users to search codebases effectively with powerful filters and syntax search options.
  • Integration with Crucible
    FishEye integrates seamlessly with Crucible, Atlassian's code review tool, making it easier to conduct code reviews and improve code quality within the same ecosystem.
  • Repository Visualization
    The tool offers visualization options to view repository activity, track changes, and understand the evolution of a project over time, aiding in project management and analysis.
  • Multiple SCM Support
    FishEye supports various source control management systems like Git, Mercurial, Subversion, CVS, and Perforce, making it versatile for different development environments.

Possible disadvantages of Atlassian Fisheye

  • Cost
    Compared to some open-source alternatives, FishEye can be relatively expensive, which might be a drawback for smaller teams or budget-conscious organizations.
  • Complexity
    The setup and configuration process can be complex, especially for teams unfamiliar with Atlassian products, potentially leading to a steeper learning curve.
  • Performance Issues
    Some users report performance slowdowns when indexing large repositories, which can affect productivity if not managed properly.
  • Limited Standalone Features
    While powerful, FishEye's full potential is often realized only when used in conjunction with other Atlassian tools, which could be limiting for users seeking a standalone solution.

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.

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.

Atlassian Fisheye videos

+ Add

Atlassian FishEye

More videos:

  • Review - Atlassian FishEye Overview Video

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

Category Popularity

0-100% (relative to Atlassian Fisheye and Hadoop)

Atlassian Fisheye

Hadoop

Git
100 100%
Git
0% 0
Databases
0 0%
Databases
100% 100
Code Collaboration
100 100%
Code Collaboration
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using Atlassian Fisheye and Hadoop. For example, how are they different and which one is better?
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Reviews

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

Atlassian Fisheye Reviews

We have no reviews of Atlassian Fisheye yet.
Be the first one to post

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

Social recommendations and mentions

Based on our record, Hadoop seems to be more popular. It has been mentiond 25 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.

Atlassian Fisheye mentions (0)

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

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 / 20 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 / 20 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 / 26 days 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
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What are some alternatives?

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

WPMU DEV - WPMU offers WordPress Plugins, WordPress Themes, WordPress Multisite and BuddyPress Plugins and Themes.

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

MAMP - MAMP is the abbreviation for Macintosh, Apache, MySQL, and PHP. It is a reliable application with its four components that allows you to access the local PHP server as well as the database server (SQL).

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

Firefox Developer Edition - Built for those who build the Web. The only browser made for developers.

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

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