AWS Data Pipeline vs Elasticsearch: What are the differences?
What is 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.
What is Elasticsearch? Open Source, Distributed, RESTful Search Engine. Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
AWS Data Pipeline can be classified as a tool in the "Data Transfer" category, while Elasticsearch is grouped under "Search as a Service".
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, Elasticsearch provides the following key features:
- Distributed and Highly Available Search Engine.
- Multi Tenant with Multi Types.
- Various set of APIs including RESTful
Elasticsearch is an open source tool with 42.4K GitHub stars and 14.2K GitHub forks. Here's a link to Elasticsearch's open source repository on GitHub.
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What is AWS Data Pipeline?
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