AWS Direct Connect vs Amazon Kinesis

Overview

AWS Direct Connect

Stacks39

Followers61

Votes0

Amazon Kinesis

Stacks796

Followers604

Votes9

AWS Direct Connect vs Amazon Kinesis: What are the differences?

AWS Direct Connect and Amazon Kinesis: Key Differences

AWS Direct Connect and Amazon Kinesis are two popular services offered by Amazon Web Services (AWS), but they serve different purposes. Here are the key differences between the two:

Purpose: AWS Direct Connect is a networking service that enables organizations to establish private and dedicated network connections between their on-premises data centers and AWS cloud infrastructure. It allows for reliable and low-latency data transfer between the two environments. On the other hand, Amazon Kinesis is a real-time data streaming and processing service. It collects, stores, and processes large volumes of streaming data from various sources such as IoT devices, clickstreams, and logs.
Data Flow: AWS Direct Connect facilitates the transfer of data between on-premises environments and AWS services. It provides a dedicated physical connection, bypassing the public internet, to ensure security, reliability, and consistent network performance. In contrast, Amazon Kinesis is designed to ingest and process streaming data from multiple sources in real-time. It allows organizations to collect and analyze data as it becomes available.
Data Types: AWS Direct Connect primarily handles data transfer between on-premises resources and AWS services, irrespective of the data type. It is suitable for transferring any kind of data, including files, databases, and virtual machine images. On the other hand, Amazon Kinesis specializes in handling continuously flowing, high-velocity, and large volumes of streaming data, such as real-time app data, video feeds, and sensor readings.
Processing Capabilities: AWS Direct Connect does not offer any processing capabilities for the transferred data. It solely focuses on establishing and managing the dedicated network connection. In contrast, Amazon Kinesis provides various tools and services for real-time data processing, such as data transformations, filtering, analytics, and integration with other AWS services like Lambda, Elasticsearch, and Redshift.
Use Cases: AWS Direct Connect is commonly used by organizations that require a private and dedicated connection to their AWS resources, such as for hybrid architectures, disaster recovery, or large data transfers. On the other hand, Amazon Kinesis is used for real-time analytics, data ingestion for big data processing, building streaming data pipelines, and creating real-time dashboards for monitoring purposes.
Pricing Model: AWS Direct Connect has a pricing model based on the port speed and the duration of usage. Organizations need to pay for the port, data transfer, and any additional data transfer requests. Amazon Kinesis, on the other hand, has a pricing model based on the number of shard hours, PUT payload units, and GET payload units. It also offers various pricing tiers for different levels of data ingestion and data processing requirements.

In summary, AWS Direct Connect enables private and dedicated network connections between on-premises environments and AWS, while Amazon Kinesis is a real-time data streaming and processing service. Direct Connect focuses on reliable data transfer, while Kinesis focuses on ingesting, processing, and analyzing streaming data.

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Advice on AWS Direct Connect, Amazon Kinesis

Roel

Lead Developer at Di-Vision Consultion

Dec 14, 2020

Decided

Use case for ingressing a lot of data and post-process the data and forward it to multiple endpoints.

Kinesis can ingress a lot of data easier without have to manage scaling in DynamoDB (ondemand would be too expensive) We looked at DynamoDB Streams to hook up with Lambda, but Kinesis provides the same, and a backup incoming data to S3 with Firehose instead of using the TTL in DynamoDB.

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Detailed Comparison

AWS Direct Connect	Amazon Kinesis
AWS Direct Connect makes it easy to establish a dedicated network connection from your premises to AWS. Using AWS Direct Connect, you can establish private connectivity between AWS and your datacenter, office, or colocation environment, which in many cases can reduce your network costs, increase bandwidth throughput, and provide a more consistent network experience than Internet-based connections.	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.
Reduces Your Bandwidth Costs – If you have bandwidth-heavy workloads that you wish to run in AWS, AWS Direct Connect reduces your network costs into and out of AWS in two ways. First, by transferring data to and from AWS directly, you can reduce your bandwidth commitment to your Internet service provider. Second, all data transferred over your dedicated connection is charged at the reduced AWS Direct Connect data transfer rate rather than Internet data transfer rates.;Consistent Network Performance – Network latency over the Internet can vary given that the Internet is constantly changing how data gets from point A to B. With AWS Direct Connect, you choose the data that utilizes the dedicated connection and how that data is routed which can provide a more consistent network experience over Internet-based connections.;Compatible with all AWS Services – AWS Direct Connect is a network service, and works with all AWS services that are accessible over the Internet, such as Amazon Simple Storage Service (Amazon S3), Elastic Compute Cloud (Amazon EC2), and Amazon Virtual Private Cloud (Amazon VPC).	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
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Stacks 39	Stacks 796
Followers 61	Followers 604
Votes 0	Votes 9
Pros & Cons
No community feedback yet	Pros 9 Scalable Cons 3 Cost

What are some alternatives to AWS Direct Connect, Amazon Kinesis?

Google Cloud Dataflow

Google Cloud Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.

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Amazon Kinesis Firehose

Amazon Kinesis Firehose is the easiest way to load streaming data into AWS. It can capture and automatically load streaming data into Amazon S3 and Amazon Redshift, enabling near real-time analytics with existing business intelligence tools and dashboards you’re already using today.

Aviatrix

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Twister2

It is a high-performance data processing framework with capabilities to handle streaming and batch data. It can leverage high-performance clusters as well we cloud services to efficiently process data.

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