AWS Data Pipeline vs AWS Storage Gateway

Overview

AWS Storage Gateway

Stacks17

Followers59

Votes0

AWS Data Pipeline

Stacks94

Followers398

Votes1

AWS Data Pipeline vs AWS Storage Gateway: What are the differences?

<Write Introduction here>

Integration with Services: AWS Data Pipeline is a service that helps in orchestrating and automating the movement and transformation of data while AWS Storage Gateway is a service that connects an on-premises software appliance with cloud-based storage to provide seamless and secure integration. While Data Pipeline focuses on data processing activities, Storage Gateway primarily focuses on storage connectivity.
Purpose: The main purpose of AWS Data Pipeline is to schedule and execute data-driven workflows while AWS Storage Gateway is designed to bridge the gap between on-premises storage systems and cloud storage, providing a seamless integration for data access and backup.
Data Processing vs Storage Connectivity: AWS Data Pipeline is more suitable for organizations looking to perform data processing activities such as data movement, transformation, and analysis, whereas AWS Storage Gateway is better suited for organizations looking to connect their on-premises storage with cloud storage for backup, disaster recovery, and scalability.
Data Transformation Capabilities: AWS Data Pipeline offers built-in data transformation activities such as data validation, formatting, and encryption, providing a comprehensive solution for data processing workflows. In comparison, AWS Storage Gateway focuses more on data transfer and storage protocols, with fewer built-in data transformation capabilities.
Resource Management: AWS Data Pipeline allows users to manage computing resources to execute data processing tasks efficiently, optimizing costs and performance. On the other hand, AWS Storage Gateway provides a seamless extension of on-premises storage to the cloud, simplifying storage management and reducing storage costs.
Scalability and Flexibility: AWS Data Pipeline offers scalability in terms of processing large volumes of data efficiently, while AWS Storage Gateway provides flexibility in terms of storage options and configurations, allowing organizations to choose the most suitable storage solutions for their needs.

In Summary, AWS Data Pipeline and AWS Storage Gateway serve different purposes within the AWS ecosystem, with Data Pipeline focusing on data processing workflows and Storage Gateway facilitating storage connectivity between on-premises and cloud environments.

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Detailed Comparison

AWS Storage Gateway	AWS Data Pipeline
The AWS Storage Gateway is a service connecting an on-premises software appliance with cloud-based storage. Once the AWS Storage Gateway’s software appliance is installed on a local host, you can mount Storage Gateway volumes to your on-premises application servers as iSCSI devices, enabling a wide variety of systems and applications to make use of them. Data written to these volumes is maintained on your on-premises storage hardware while being asynchronously backed up to AWS, where it is stored in Amazon Glacier or in Amazon S3 in the form of Amazon EBS snapshots. Snapshots are encrypted to make sure that customers do not have to worry about encrypting sensitive data themselves. When customers need to retrieve data, they can restore snapshots locally, or create Amazon EBS volumes from snapshots for use with applications running in Amazon EC2. It provides low-latency performance by maintaining frequently accessed data on-premises while securely storing all of your data encrypted.	AWS Data Pipeline is a web service that provides a simple management system for data-driven workflows. Using AWS Data Pipeline, you define a pipeline composed of the “data sources” that contain your data, the “activities” or business logic such as EMR jobs or SQL queries, and the “schedule” on which your business logic executes. For example, you could define a job that, every hour, runs an Amazon Elastic MapReduce (Amazon EMR)–based analysis on that hour’s Amazon Simple Storage Service (Amazon S3) log data, loads the results into a relational database for future lookup, and then automatically sends you a daily summary email.
Gateway-Cached Volumes – Gateway-Cached volumes allow you to utilize Amazon S3 for your primary data, while retaining some portion of it locally in a cache for frequently accessed data.;Gateway-Stored Volumes – Gateway-Stored volumes store your primary data locally, while asynchronously backing up that data to AWS.;Data Snapshots – Gateway-Cached volumes and Gateway-Stored volumes provide the ability to create and store point-in-time snapshots of your storage volumes in Amazon S3.;Gateway-VTL – Gateway-VTL provides you with a cost-effective, scalable, and durable virtual tape infrastructure that allows you to eliminate the challenges associated with owning and operating an on-premises physical tape infrastructure.;Secure – The AWS Storage Gateway securely transfers your data to AWS over SSL and stores data encrypted at rest in Amazon S3 and Amazon Glacier using Advanced Encryption Standard (AES) 256, a secure symmetric-key encryption standard using 256-bit encryption keys.;Durably backed by Amazon S3 and Amazon Glacier –The AWS Storage Gateway durably stores your on-premises application data by uploading it to Amazon S3 and Amazon Glacier. Amazon S3 and Amazon Glacier redundantly store data in multiple facilities and on multiple devices within each facility. Amazon S3 and Amazon Glacier also perform regular, systematic data integrity checks and are built to be automatically self-healing.;Compatible – There is no need to re-architect your on-premises applications. Gateway-Cached volumes and Gateway-Stored volumes expose a standard iSCSI block disk device interface and Gateway-VTL presents a standard iSCSI virtual tape library interface.	You can find (and use) a variety of popular AWS Data Pipeline tasks in the AWS Management Console’s template section.;Hourly analysis of Amazon S3‐based log data;Daily replication of AmazonDynamoDB data to Amazon S3;Periodic replication of on-premise JDBC database tables into RDS
Statistics
Stacks 17	Stacks 94
Followers 59	Followers 398
Votes 0	Votes 1
Pros & Cons
No community feedback yet	Pros 1 Easy to create DAG and execute it

What are some alternatives to AWS Storage Gateway, AWS Data Pipeline?

Amazon Glacier

In order to keep costs low, Amazon Glacier is optimized for data that is infrequently accessed and for which retrieval times of several hours are suitable. With Amazon Glacier, customers can reliably store large or small amounts of data for as little as $0.01 per gigabyte per month, a significant savings compared to on-premises solutions.

AWS Snowball Edge

AWS Snowball Edge is a 100TB data transfer device with on-board storage and compute capabilities. You can use Snowball Edge to move large amounts of data into and out of AWS, as a temporary storage tier for large local datasets, or to support local workloads in remote or offline locations.

Requests

It is an elegant and simple HTTP library for Python, built for human beings. It allows you to send HTTP/1.1 requests extremely easily. There’s no need to manually add query strings to your URLs, or to form-encode your POST data.

NPOI

It is a .NET library that can read/write Office formats without Microsoft Office installed. No COM+, no interop.

HTTP/2

It's focus is on performance; specifically, end-user perceived latency, network and server resource usage.

Embulk

It is an open-source bulk data loader that helps data transfer between various databases, storages, file formats, and cloud services.

restic

It is a backup program that is fast, efficient and secure. It uses cryptography to guarantee the confidentiality and integrity of your data.

Veeam Backup & Replication

It is industry-leading Backup & Replication software. It delivers availability for all your cloud, virtual and physical workloads. Through a simple-by-design management console, you can easily achieve fast, flexible and reliable backup, recovery and replication for all your applications and data.

Borg

It is a deduplicating backup program. It provides an efficient and secure way to backup data. The data deduplication technique used makes it suitable for daily backups since only changes are stored. The authenticated encryption technique makes it suitable for backups to not fully trusted targets.

Google BigQuery Data Transfer Service

BigQuery Data Transfer Service lets you focus your efforts on analyzing your data. You can setup a data transfer with a few clicks. Your analytics team can lay the foundation for a data warehouse without writing a single line of code.

Related Comparisons

AWS Data Pipeline vs AWS Storage Gateway: What are the differences?

<Write Introduction here>

Integration with Services: AWS Data Pipeline is a service that helps in orchestrating and automating the movement and transformation of data while AWS Storage Gateway is a service that connects an on-premises software appliance with cloud-based storage to provide seamless and secure integration. While Data Pipeline focuses on data processing activities, Storage Gateway primarily focuses on storage connectivity.
Purpose: The main purpose of AWS Data Pipeline is to schedule and execute data-driven workflows while AWS Storage Gateway is designed to bridge the gap between on-premises storage systems and cloud storage, providing a seamless integration for data access and backup.
Data Processing vs Storage Connectivity: AWS Data Pipeline is more suitable for organizations looking to perform data processing activities such as data movement, transformation, and analysis, whereas AWS Storage Gateway is better suited for organizations looking to connect their on-premises storage with cloud storage for backup, disaster recovery, and scalability.
Data Transformation Capabilities: AWS Data Pipeline offers built-in data transformation activities such as data validation, formatting, and encryption, providing a comprehensive solution for data processing workflows. In comparison, AWS Storage Gateway focuses more on data transfer and storage protocols, with fewer built-in data transformation capabilities.
Resource Management: AWS Data Pipeline allows users to manage computing resources to execute data processing tasks efficiently, optimizing costs and performance. On the other hand, AWS Storage Gateway provides a seamless extension of on-premises storage to the cloud, simplifying storage management and reducing storage costs.
Scalability and Flexibility: AWS Data Pipeline offers scalability in terms of processing large volumes of data efficiently, while AWS Storage Gateway provides flexibility in terms of storage options and configurations, allowing organizations to choose the most suitable storage solutions for their needs.

AWS Data Pipeline vs AWS Storage Gateway

Overview