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  5. AWS Data Pipeline vs PieSync

AWS Data Pipeline vs PieSync

OverviewComparisonAlternatives

Overview

AWS Data Pipeline
AWS Data Pipeline
Stacks94
Followers398
Votes1
PieSync
PieSync
Stacks11
Followers13
Votes0

AWS Data Pipeline vs PieSync: What are the differences?

Introduction: AWS Data Pipeline and PieSync are two popular data integration tools that help streamline data movement and synchronization between different systems and applications. Despite having similar objectives, there are key differences between these tools that set them apart in terms of functionality and use cases.

  1. Data Source Compatibility: AWS Data Pipeline is designed to work seamlessly with various data sources, including Amazon S3, RDS, DynamoDB, and Redshift. In contrast, PieSync offers more flexibility by supporting a wider range of applications and tools beyond the AWS ecosystem, such as CRMs, marketing platforms, and other SaaS applications.

  2. Automation Capabilities: While both tools offer automation features, AWS Data Pipeline is more focused on orchestrating complex data processing workflows and data transformation tasks within the AWS environment. On the other hand, PieSync specializes in real-time, two-way data syncing between different apps, enabling users to automatically update and synchronize data across multiple platforms.

  3. Data Transformation Options: AWS Data Pipeline provides a wide range of built-in activities and pre-configured templates for data transformation tasks, such as data cleansing, transformation, and aggregation. PieSync, on the other hand, offers mapping and filtering options that allow users to customize how data is synced between different applications based on specific criteria and rules.

  4. Cost Structure: AWS Data Pipeline follows a pay-as-you-go pricing model based on the usage of pipeline instances and data processing resources within the AWS cloud. In contrast, PieSync offers subscription-based pricing plans that are typically based on the number of applications being synced and the volume of data being transferred between them.

  5. Ease of Use and Integration: AWS Data Pipeline is well-suited for users who are already familiar with the AWS environment and prefer a more technical approach to data integration and processing. PieSync, on the other hand, is known for its intuitive user interface and easy setup process, making it ideal for non-technical users who want a simple solution for data synchronization between different applications.

In Summary, AWS Data Pipeline and PieSync differ in terms of data source compatibility, automation capabilities, data transformation options, cost structure, and ease of use, catering to different user needs and preferences in the realm of data integration and synchronization.

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Detailed Comparison

AWS Data Pipeline
AWS Data Pipeline
PieSync
PieSync

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.

A cloud-based solution engineered to fill the gaps between cloud applications. The software utilizes Intelligent 2-way Contact Sync technology to sync contacts in real-time between your favorite CRM and marketing apps.

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
Sync any app; Real-time and two syncing; Custom mapping; Unlimited rules; Personalized account setup; Custom integration; Dedicated account manager.
Statistics
Stacks
94
Stacks
11
Followers
398
Followers
13
Votes
1
Votes
0
Pros & Cons
Pros
  • 1
    Easy to create DAG and execute it
No community feedback yet
Integrations
No integrations available
HubSpot
HubSpot
Stripe
Stripe
Mailchimp
Mailchimp
Salesforce Commerce Cloud
Salesforce Commerce Cloud
Zendesk
Zendesk
Zapier
Zapier
Recurly
Recurly
Insightly
Insightly
Nimble
Nimble
Xero
Xero

What are some alternatives to AWS Data Pipeline, PieSync?

AWS Snowball Edge

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

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

NPOI

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

HTTP/2

HTTP/2

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

Embulk

Embulk

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

Google BigQuery Data Transfer Service

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.

Resilio

Resilio

It offers the industry leading data synchronization tool. Trusted by millions of users and thousands of companies across the globe. Resilient, fast and scalable p2p file sync software for enterprises and individuals.

Synth

Synth

It is the quickest way to create accurate synthetic clones of your entire data infrastructure. It creates end-to-end synthetic data environments that look and behave exactly like your production data. Down to your data's content and database version.

Flatfile

Flatfile

The drop-in data importer that implements in hours, not weeks. Give your users the import experience you always dreamed of, but never had time to build.

AWS Import/Export

AWS Import/Export

Import/Export supports importing and exporting data into and out of Amazon S3 buckets. For significant data sets, AWS Import/Export is often faster than Internet transfer and more cost effective than upgrading your connectivity.

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