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Atlassian Fisheye VS Amazon EMR

Compare Atlassian Fisheye VS Amazon EMR 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.

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
  • Atlassian Fisheye Landing page
    Landing page //
    2023-08-04
  • Amazon EMR Landing page
    Landing page //
    2023-04-02

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.

Amazon EMR features and specs

  • Scalability
    Amazon EMR makes it easy to provision one, hundreds, or thousands of compute instances in minutes. You can easily scale your cluster up or down based on your needs.
  • Cost-effectiveness
    You only pay for what you use with EMR. There are no upfront fees. You can also leverage EC2 Spot Instances for a more cost-effective solution.
  • Ease of Use
    Amazon EMR has a user-friendly interface and integrates with a wide range of AWS services, making it easy to set up and manage big data frameworks like Apache Hadoop, Spark, etc.
  • Managed Service
    Amazon EMR takes care of the setup, configuration, and tuning of the big data environments, allowing you to focus on your data processing rather than managing infrastructure.
  • Security
    EMR integrates with AWS security features such as IAM for fine-grained access control, encryption options, and Virtual Private Cloud (VPC) for network security.
  • Flexibility
    Supports multiple big data frameworks including Hadoop, Spark, HBase, Presto, and more, facilitating a wide range of use cases.

Possible disadvantages of Amazon EMR

  • Complex Pricing Model
    EMR's pricing can be complex with costs varying based on instance types, storage, and data transfer. Predicting costs may be challenging.
  • Data Transfer Costs
    If your applications require transferring large amounts of data in and out of EMR, the associated costs can be significant.
  • Learning Curve
    Although EMR is easier to manage compared to on-premises solutions, there is still a learning curve associated with mastering the service and optimizing its various settings.
  • Vendor Lock-in
    Since EMR is an AWS service, you may find it difficult to migrate to another service or cloud provider without significant re-engineering.
  • Dependency on AWS Ecosystem
    The full potential of EMR is best realized when integrated with other AWS services. This can be limiting if your architecture uses services from multiple cloud providers.

Analysis of Amazon EMR

Overall verdict

  • Yes, Amazon EMR is generally considered a good option for organizations that need to handle large-scale data processing and analysis. Its integration with the AWS ecosystem, flexibility in resource management, and support for a wide array of big data frameworks make it a strong contender in the cloud-based big data processing market.

Why this product is good

  • Amazon EMR (Elastic MapReduce) is a robust cloud service provided by AWS for processing and analyzing large datasets quickly and cost-effectively. It simplifies running big data frameworks like Apache Hadoop and Apache Spark on AWS, offering scalability, flexibility, and integration with other AWS services. EMR is favored for its ability to dynamically allocate resources, thus optimizing both performance and cost for big data processing needs.

Recommended for

    Amazon EMR is recommended for data engineers, data scientists, and IT professionals who need to manage and process large datasets in a scalable, efficient, and cost-effective manner. It is especially suitable for businesses that are already using AWS services and want to leverage a tightly integrated ecosystem. Additionally, it is a good choice for organizations that require rapid and flexible data analysis capabilities provided by frameworks such as Hadoop, Spark, HBase, and Presto.

Atlassian Fisheye videos

+ Add

Atlassian FishEye

More videos:

  • Review - Atlassian FishEye Overview Video

Amazon EMR videos

+ Add

Amazon EMR Masterclass

More videos:

  • Review - Deep Dive into What’s New in Amazon EMR - AWS Online Tech Talks
  • Tutorial - How to use Apache Hive and DynamoDB using Amazon EMR

Category Popularity

0-100% (relative to Atlassian Fisheye and Amazon EMR)

Atlassian Fisheye

Amazon EMR

Git
100 100%
Git
0% 0
Data Dashboard
0 0%
Data Dashboard
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 Amazon EMR. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Amazon EMR seems to be more popular. It has been mentiond 10 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.

Amazon EMR mentions (10)

  • 5 Best Practices For Data Integration To Boost ROI And Efficiency
    There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 2 years ago
  • What compute service i should use? Advice for a duck-tape kind of guy
    I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 3 years ago
  • Processing a large text file containing millions of records.
    This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 3 years ago
  • How to use Spark and Pandas to prepare big data
    Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 3 years ago
  • Beginner building a Hadoop cluster
    Check out https://aws.amazon.com/emr/. Source: about 3 years ago
View more

What are some alternatives?

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

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

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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).

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

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

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

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