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  5. AWS Data Pipeline vs Stream

AWS Data Pipeline vs Stream

OverviewComparisonAlternatives

Overview

AWS Data Pipeline
AWS Data Pipeline
Stacks94
Followers398
Votes1
Stream
Stream
Stacks290
Followers226
Votes54

AWS Data Pipeline vs Stream: What are the differences?

AWS Data Pipeline: Process and move data between different AWS compute and storage services. 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; Stream: Build scalable feeds, activity streams & chat in a few hours instead of months. Stream allows you to build scalable feeds, activity streams, and chat. Stream’s simple, yet powerful API’s and SDKs are used by some of the largest and most popular applications for feeds and chat. SDKs available for most popular languages.

AWS Data Pipeline and Stream are primarily classified as "Data Transfer" and "Activity Feeds as a Service" tools respectively.

Some of the features offered by AWS Data Pipeline are:

  • 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

On the other hand, Stream provides the following key features:

  • Activity, Notification & Personalized Feeds
  • Real-Time Chat
  • Multi-Region Support

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Detailed Comparison

AWS Data Pipeline
AWS Data Pipeline
Stream
Stream

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.

Stream allows you to build scalable feeds, activity streams, and chat. Stream’s simple, yet powerful API’s and SDKs are used by some of the largest and most popular applications for feeds and chat. SDKs available for most popular languages.

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
Activity, Notification & Personalized Feeds; Real-Time Chat; Multi-Region Support; High Availability; SDKs & Components;
Statistics
Stacks
94
Stacks
290
Followers
398
Followers
226
Votes
1
Votes
54
Pros & Cons
Pros
  • 1
    Easy to create DAG and execute it
Pros
  • 18
    Integrates via easy-to-use REST API
  • 18
    It's easy to setup with the minimum coding
  • 18
    Up and running in few minutes
Integrations
No integrations available
Rails
Rails
Django
Django
PHP
PHP
Java
Java
Scala
Scala
Node.js
Node.js
Ruby
Ruby
Golang
Golang
Python
Python
Parse
Parse

What are some alternatives to AWS Data Pipeline, Stream?

Oneprofile

Oneprofile

Oneprofile syncs customer profiles and events across all the tools a company uses. Instead of each system having its own version of a customer, Oneprofile keeps everything in sync automatically — CRMs, analytics, support, marketing. When customer data changes anywhere, it’s reflected everywhere, instantly. No manual pipelines, no broken integrations — just the right data in the right place.

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.

ShipUpdate

ShipUpdate

Is a lightweight changelog tool that helps SaaS teams publish product updates and display them instantly on their website with a simple changelog widget.

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.

Blink

Blink

It empowers and protects your most important people with the information and tools they need. Its Direct & Group Messaging means you can reach anyone, anytime, without the need for email addresses or phone numbers.

PieSync

PieSync

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.

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