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Amazon EMR VS JSON Server

Compare Amazon EMR VS JSON Server and see what are their differences

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

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

JSON Server logo JSON Server

Get a full fake REST API with zero coding in less than 30 seconds. For front-end developers who need a quick back-end for prototyping and mocking
  • Amazon EMR Landing page
    Landing page //
    2023-04-02
  • JSON Server Landing page
    Landing page //
    2023-08-01

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.

JSON Server features and specs

  • Ease of Setup
    JSON Server can be set up quickly with minimal configuration, making it ideal for prototyping and rapid development. It allows developers to have a fully functioning REST API within minutes.
  • RESTful API
    It provides a standard RESTful API out of the box, allowing developers to perform all CRUD operations. This is helpful for simulating a real-world server while testing client-side applications.
  • Customization
    JSON Server supports middlewares, routes, and custom rules, allowing developers to customize the behavior and structure of the API to better suit their needs.
  • Fakes Backend Data
    It's great for simulating backend responses without needing a real backend setup, useful in front-end development to test components and interactions.
  • Lightweight
    As a lightweight server, it requires fewer resources and is quite simple compared to setting up a full-fledged backend server.

Possible disadvantages of JSON Server

  • Not for Production
    JSON Server is designed for development and testing. It is not suitable for production use due to performance limits and lack of robust security features.
  • Limited Functionality
    While JSON Server is great for basic CRUD operations, it lacks advanced features like authentication, authorization, and complex querying.
  • Data Persistence
    Data is stored in a JSON file, and while this is convenient for testing, it is not suitable for applications that require persistent and scalable data storage.
  • In-memory Limitations
    Being an in-memory server, it may have issues with handling large datasets or complex data structures efficiently.
  • Manual Data Reset
    Any changes made to the JSON file while the server is running require manual resets or reloads to reflect in the API, which can be cumbersome during continuous development cycles.

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.

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

JSON Server videos

+ Add

Angular CRUD with Web API Tutorial Part #3 - Setup Local JSON Server and Mock API Endpoints

Category Popularity

0-100% (relative to Amazon EMR and JSON Server)

Amazon EMR

JSON Server

Data Dashboard
100 100%
Data Dashboard
0% 0
Development
31 31%
Development
69% 69
Big Data
100 100%
Big Data
0% 0
API Tools
0 0%
API Tools
100% 100

User comments

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Social recommendations and mentions

Based on our record, JSON Server should be more popular than Amazon EMR. It has been mentiond 45 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.

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: over 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

JSON Server mentions (45)

  • Building a CRUD app with React Query, TypeScript, and Axios
    We'll be using json-server to create the REST API that we'll fetch data from. In the root of the project, create a db.json file with the contents. - Source: dev.to / about 1 year ago
  • Full Stack To Do list, a step-by-step tutorial
    Our backend will be little more than a two-way translation layer between the database and the user interface (UI). Later in this post we will identify other responsibilities of a backend but our implementation will be kept simple to demonstrate the fundamental machinery and concepts. It is worth noting the backend comes in two parts, web server and application server. Both json-server and Express are able to... - Source: dev.to / almost 2 years ago
  • Improve Frontend-Backend development harmony with JSON-Server
    JSON-Server creates fake REST API with a minimum amount of configuration, it provides a simple way to create mock RESTful APIs and easily define the required endpoints, allows easy definition of the data schema in a JSON file and can serve as a reference for each figure in the project. - Source: dev.to / about 2 years ago
  • Dictionary app
    I thought about usingJson Server (hosting the repo with the words on Github to begin with), Googlesheets, or maybe Firestore (i would prefer not to use it ,to avoid extra costs just in case it gets a reasonable amount of users). It isnt a big app so I just want a simple solution for storing the words and fetching them. Source: about 2 years ago
  • Playwright - Not just for Frontend
    First, I didn't create a backend API for this example, but I used a fake API to test. I created it with json-server and json-server-auth. They are two npm packages that use a JSON file as a database and expose the database in an API. You can find more about json-server in its documentation and about json-server-auth here. - Source: dev.to / over 2 years ago
View more

What are some alternatives?

When comparing Amazon EMR and JSON Server, you can also consider the following products

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

JSON Placeholder - JSON Placeholder is a modern platform that provides you online REST API, which you can instantly use whenever you need any fake data.

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

mocki Fake JSON API - mocki Fake JSON API is an advanced platform that offers you to create API for personal use or testing purposes.

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

Mockae - The most flexible way to mock REST APIs with Lua code execution

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