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  5. Amazon Kinesis vs Postman

Amazon Kinesis vs Postman

OverviewDecisionsComparisonAlternatives

Overview

Amazon Kinesis
Amazon Kinesis
Stacks795
Followers604
Votes9
Postman
Postman
Stacks96.1K
Followers82.5K
Votes1.8K
Forks0

Amazon Kinesis vs Postman: What are the differences?

  1. Key difference 1: Architecture and purpose: Amazon Kinesis and Postman serve different purposes and are designed with different architectures. Amazon Kinesis is a fully managed service that allows real-time data streaming for big data analytics and processing. It is optimized for high throughput and horizontal scalability, making it suitable for data-intensive applications. On the other hand, Postman is a collaboration platform for API development and testing. It provides tools for API documentation, testing, and monitoring, helping developers streamline the API development process.

  2. Key difference 2: Data processing capabilities: Another significant difference between Amazon Kinesis and Postman lies in their data processing capabilities. Amazon Kinesis offers real-time data processing and analytics, enabling users to collect, process, and analyze large volumes of streaming data in real-time. It provides features like data transformations, real-time analytics, and integration with other AWS services. In contrast, Postman focuses more on API testing and monitoring rather than data processing. It offers features like request scripting, automated testing, and performance monitoring for APIs.

  3. Key difference 3: Scalability and performance: When it comes to scalability and performance, Amazon Kinesis has the advantage due to its architecture and purpose. It is built to handle massive workloads and scale horizontally to accommodate increasing data streams and processing requirements. Amazon Kinesis can handle unlimited data streams with high throughput and low latency. On the other hand, while Postman offers features like load testing and performance monitoring for APIs, it may not be suitable for handling large-scale data processing tasks with the same performance and scalability as Amazon Kinesis.

  4. Key difference 4: Management and maintenance: Amazon Kinesis is a fully managed service provided by AWS, which means that AWS handles infrastructure management, maintenance, and backups. Users only need to configure their data streams and define the processing logic. It simplifies the operational overhead and reduces the need for manual maintenance. In contrast, Postman is a developer tool that requires users to set up and manage their own environment. It needs to be installed on the user's machine, and users are responsible for keeping it up-to-date and managing their API collections.

  5. Key difference 5: Integration and ecosystem: Amazon Kinesis is part of the comprehensive AWS ecosystem, which includes various cloud services such as storage (Amazon S3), analytics (Amazon Redshift), and serverless computing (AWS Lambda). It seamlessly integrates with other AWS services, allowing users to build scalable and powerful data processing pipelines. On the other hand, while Postman provides integrations with popular development tools and platforms, it does not offer the same level of integration with cloud services or ecosystem as Amazon Kinesis.

  6. Key difference 6: Pricing model: Finally, the pricing models for Amazon Kinesis and Postman differ significantly. Amazon Kinesis pricing is primarily based on the volume of data ingested, data transferred, and data analyzed. The pricing scales with usage, and users only pay for what they use. On the other hand, Postman offers a subscription-based pricing model, where users pay a fixed monthly or annual fee for access to certain features and additional support. The pricing is not directly tied to data processing or usage.

In summary, Amazon Kinesis is a fully managed service optimized for real-time data streaming and processing, offering scalability, high performance, and integration with the AWS ecosystem. Postman, on the other hand, is a collaboration platform for API development and testing, focusing on API testing, monitoring, and documentation.

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Advice on Amazon Kinesis, Postman

Jagdeep
Jagdeep

Tech Lead at Founder and Lightning

May 6, 2019

ReviewonPostmanPostman

I use Postman because of the ease of team-management, using workspaces and teams, runner, collections, environment variables, test-scripts (post execution), variable management (pre and post execution), folders (inside collections, for better management of APIs), newman, easy-ci-integration (and probably a few more things that I am not able to recall right now).

411k views411k
Comments
StackShare
StackShare

May 1, 2019

Needs advice

From a StackShare Community member: "I just started working for a start-up and we are in desperate need of better documentation for our API. Currently our API docs is in a README.md file. We are evaluating Postman and Swagger UI. Since there are many options and I was wondering what other StackSharers would recommend?"

382k views382k
Comments
Stephen
Stephen

Artificial Intelligence Fellow

Feb 4, 2020

Decided

Postman supports automation and organization in a way that Insomnia just doesn't. Admittedly, Insomnia makes it slightly easy to query the data that you get back (in a very MongoDB-esque query language) but Postman sets you up to develop the code that you would use in development/testing right in the editor.

361k views361k
Comments

Detailed Comparison

Amazon Kinesis
Amazon Kinesis
Postman
Postman

Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.

It is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide.

Real-time Processing- Amazon Kinesis enables you to collect and analyze information in real-time, allowing you to answer questions about the current state of your data, from inventory levels to stock trade frequencies, rather than having to wait for an out-of-date report;Easy to use- You can create a new stream, set the throughput requirements, and start streaming data quickly and easily. Amazon Kinesis automatically provisions and manages the storage required to reliably and durably collect your data stream;High throughput. Elastic.- Amazon Kinesis seamlessly scales to match the data throughput rate and volume of your data, from megabytes to terabytes per hour. Amazon Kinesis will scale up or down based on your needs;Integrate with Amazon S3, Amazon Redshift, and Amazon DynamoDB- With Amazon Kinesis, you can reliably collect, process, and transform all of your data in real-time before delivering it to data stores of your choice, where it can be used by existing or new applications. Connectors enable integration with Amazon S3, Amazon Redshift, and Amazon DynamoDB;Build Kinesis Applications- Amazon Kinesis provides developers with client libraries that enable the design and operation of real-time data processing applications. Just add the Amazon Kinesis Client Library to your Java application and it will be notified when new data is available for processing;Low Cost- Amazon Kinesis is cost-efficient for workloads of any scale. You can pay as you go, and you’ll only pay for the resources you use. You can get started by provisioning low throughput streams, and only pay a low hourly rate for the throughput you need
Compact layout;HTTP requests with file upload support;Formatted API responses for JSON and XML;Image previews;Request history;Basic Auth, OAuth 1.0, OAuth 2.0, and other common auth helpers;Autocomplete for URL and header values;Key/value editors for adding parameters or header values. Works for URL parameters too.;Use environment variables to easily shift between settings. Great for testing production, staging or local setups.;Keyboard shortcuts to maximize your productivity;Automatically generated web documentation;Mock servers hosted on Postman’s cloud;API monitoring run from Postman cloud
Statistics
GitHub Forks
-
GitHub Forks
0
Stacks
795
Stacks
96.1K
Followers
604
Followers
82.5K
Votes
9
Votes
1.8K
Pros & Cons
Pros
  • 9
    Scalable
Cons
  • 3
    Cost
Pros
  • 490
    Easy to use
  • 369
    Great tool
  • 276
    Makes developing rest api's easy peasy
  • 156
    Easy setup, looks good
  • 144
    The best api workflow out there
Cons
  • 10
    Stores credentials in HTTP
  • 9
    Bloated features and UI
  • 8
    Cumbersome to switch authentication tokens
  • 7
    Poor GraphQL support
  • 5
    Expensive
Integrations
No integrations available
HipChat
HipChat
Keen
Keen
Slack
Slack
Dropbox
Dropbox
Datadog
Datadog
PagerDuty
PagerDuty
Bigpanda
Bigpanda
Microsoft Teams
Microsoft Teams
Newman
Newman
VictorOps
VictorOps

What are some alternatives to Amazon Kinesis, Postman?

Swagger UI

Swagger UI

Swagger UI is a dependency-free collection of HTML, Javascript, and CSS assets that dynamically generate beautiful documentation and sandbox from a Swagger-compliant API

Paw

Paw

Paw is a full-featured and beautifully designed Mac app that makes interaction with REST services delightful. Either you are an API maker or consumer, Paw helps you build HTTP requests, inspect the server's response and even generate client code.

Apiary

Apiary

It takes more than a simple HTML page to thrill your API users. The right tools take weeks of development. Weeks that apiary.io saves.

Karate DSL

Karate DSL

Combines API test-automation, mocks and performance-testing into a single, unified framework. The BDD syntax popularized by Cucumber is language-neutral, and easy for even non-programmers. Besides powerful JSON & XML assertions, you can run tests in parallel for speed - which is critical for HTTP API testing.

ReadMe.io

ReadMe.io

It is an easy-to-use tool to help you build out documentation! Each documentation site that you publish is a project where there is space for documentation, interactive API reference guides, a changelog, and much more.

Appwrite

Appwrite

Appwrite's open-source platform lets you add Auth, DBs, Functions and Storage to your product and build any application at any scale, own your data, and use your preferred coding languages and tools.

Runscope

Runscope

Keep tabs on all aspects of your API's performance with uptime monitoring, integration testing, logging and real-time monitoring.

Insomnia REST Client

Insomnia REST Client

Insomnia is a powerful REST API Client with cookie management, environment variables, code generation, and authentication for Mac, Window, and Linux.

RAML

RAML

RESTful API Modeling Language (RAML) makes it easy to manage the whole API lifecycle from design to sharing. It's concise - you only write what you need to define - and reusable. It is machine readable API design that is actually human friendly.

Docusaurus

Docusaurus

Docusaurus is a project for easily building, deploying, and maintaining open source project websites.

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