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  1. Stackups
  2. Application & Data
  3. Infrastructure as a Service
  4. Dns Management
  5. Amazon Route 53 vs baikal

Amazon Route 53 vs baikal

OverviewComparisonAlternatives

Overview

Amazon Route 53
Amazon Route 53
Stacks14.5K
Followers9.4K
Votes678
baikal
baikal
Stacks4
Followers11
Votes0
GitHub Stars590
Forks30

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Detailed Comparison

Amazon Route 53
Amazon Route 53
baikal
baikal

Amazon Route 53 is designed to give developers and businesses an extremely reliable and cost effective way to route end users to Internet applications by translating human readable names like www.example.com into the numeric IP addresses like 192.0.2.1 that computers use to connect to each other. Route 53 effectively connects user requests to infrastructure running in Amazon Web Services (AWS) – such as an Amazon Elastic Compute Cloud (Amazon EC2) instance, an Amazon Elastic Load Balancer, or an Amazon Simple Storage Service (Amazon S3) bucket – and can also be used to route users to infrastructure outside of AWS.

It is a graph-based, functional API for building complex machine learning pipelines of objects that implement the scikit-learn API. It is mostly inspired on the excellent Keras API for Deep Learning, and borrows a few concepts from the TensorFlow framework and the (perhaps lesser known) graphkit package. It aims to provide an API that allows to build complex, non-linear machine learning pipelines.

Highly Available and Reliable – Route 53 is built using AWS’s highly available and reliable infrastructure. The distributed nature of our DNS servers helps ensure a consistent ability to route your end users to your application. Route 53 is designed to provide the level of dependability required by important applications. Amazon Route 53 is backed by the Amazon Route 53 Service Level Agreement.;Scalable – Route 53 is designed to automatically scale to handle very large query volumes without any intervention from you.;Designed for use with other Amazon Web Services – Route 53 is designed to work well with other AWS features and offerings. You can use Route 53 to map domain names to your Amazon EC2 instances, Amazon S3 buckets, Amazon CloudFront distributions, and other AWS resources. By using the AWS Identity and Access Management (IAM) service with Route 53, you get fine grained control over who can update your DNS data. You can use Route 53 to map your zone apex (example.com versus www.example.com) to your Elastic Load Balancing instance or Amazon S3 website bucket using a feature called Alias record.;Simple – With self-service sign-up, Route 53 can start to answer your DNS queries within minutes. You can configure your DNS settings with the AWS Management Console or our easy-to-use API. You can also programmatically integrate the Route 53 API into your overall web application. For instance, you can use Route 53’s API to create a new DNS record whenever you create a new EC2 instance.;Fast – Using a global anycast network of DNS servers around the world, Route 53 is designed to automatically route your users to the optimal location depending on network conditions. As a result, the service offers low query latency for your end users, as well as low update latency for your DNS record management needs.;Cost-Effective – Route 53 passes on the benefits of AWS’s scale to you. You pay only for managing domains through the service and the number of queries that the service answers for each of your domains, at a low cost and without minimum usage commitments or any up-front fees.;Secure – By integrating Route 53 with AWS Identity and Access Management (IAM), you can grant unique credentials and manage permissions for every user within your AWS account and specify who has access to which parts of the Route 53 service.;Flexible – Route 53 offers Weighted Round-Robin (WRR), also known as DNS load balancing. This lets you assign weights to your DNS records that specify what portion of your traffic is routed to various endpoints.
Build non-linear pipelines effortlessly; Handle multiple inputs and outputs; Add steps that operate on targets as part of the pipeline; Nest pipelines; Use prediction probabilities (or any other kind of output) as inputs to other steps in the pipeline; Query intermediate outputs, easing debugging; Freeze steps that do not require fitting; Define and add custom steps easily; Plot pipelines
Statistics
GitHub Stars
-
GitHub Stars
590
GitHub Forks
-
GitHub Forks
30
Stacks
14.5K
Stacks
4
Followers
9.4K
Followers
11
Votes
678
Votes
0
Pros & Cons
Pros
  • 185
    High-availability
  • 148
    Simple
  • 103
    Backed by amazon
  • 76
    Fast
  • 54
    Auhtoritive dns servers are spread over different tlds
Cons
  • 2
    Geo-based routing only works with AWS zones
  • 2
    SLOW
  • 1
    Restrictive rate limit
No community feedback yet
Integrations
No integrations available
Python
Python
scikit-learn
scikit-learn

What are some alternatives to Amazon Route 53, baikal?

TensorFlow

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

DNSimple

DNSimple

DNSimple provides the tools you need to manage your domains. We offer both a carefully crafted web interface for managing your domains and DNS records, as well as an HTTP API with various code libraries and tools. Buy, connect, operate!

scikit-learn

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

Google Cloud DNS

Google Cloud DNS

Use Google's infrastructure for production quality, high volume DNS serving. Your users will have reliable, low-latency access to Google's infrastructure from anywhere in the world using our network of Anycast name servers.

PyTorch

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Dyn

Dyn

An all-in-one Managed DNS service for your registered domain names. Dyn DNS is the perfect solution for your domain name’s DNS needs, whether it is for personal or business use. It gives you complete control over your DNS zone and its associated DNS records, complete with a simple DNS management web interface.

Keras

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

DNS Made Easy

DNS Made Easy

DNS Made Easy is a subsidiary of Tiggee LLC, and is a world leader in providing global IP Anycast enterprise DNS services. DNS Made Easy is currently ranked the fastest provider for 8 consecutive months and the most reliable provider.

Kubeflow

Kubeflow

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

TensorFlow.js

TensorFlow.js

Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API

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