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What is Etleap?

Etleap was developed on AWS to facilitate the integration of data warehouses and lakes like Redshift, Snowflake, and S3/Glue. Their offering streamlines and automates the ETL process through a fully-managed service. With Etleap's intuitive data wrangler, users can manage data transformations for analysis without any coding required. Additionally, Etleap keeps a close eye on data pipelines to ensure their availability and integrity. This proactive management reduces the need for ongoing maintenance and consolidates data from over 50 distinct sources into a unified database warehouse or data lake. Ultimately, Etleap enhances data accessibility and usability for businesses aiming to leverage their data effectively.

What is AWS Glue?

AWS Glue is a fully managed, serverless solution tailored for data integration, facilitating the easy discovery, preparation, and merging of data for a variety of applications, including analytics, machine learning, and software development. The service incorporates all essential functionalities for effective data integration, allowing users to conduct data analysis and utilize insights in a matter of minutes, significantly reducing the timeline from months to mere moments. The data integration workflow comprises several stages, such as identifying and extracting data from multiple sources, followed by the processes of enhancing, cleaning, normalizing, and merging the data before it is systematically organized in databases, data warehouses, and data lakes. Various users, each with their specific tools, typically oversee these distinct responsibilities, ensuring a comprehensive approach to data management. By operating within a serverless framework, AWS Glue removes the burden of infrastructure management from its users, as it automatically provisions, configures, and scales the necessary resources for executing data integration tasks. This feature allows organizations to concentrate on gleaning insights from their data instead of grappling with operational challenges. In addition to streamlining data workflows, AWS Glue also fosters collaboration and productivity among teams, enabling businesses to respond swiftly to changing data needs. The overall efficiency gained through this service positions companies to thrive in today’s data-driven environment.

Media

Media

Integrations Supported

Orchestra
Alex Solutions
Amazon Aurora
Amazon EC2
Amazon Redshift
DataBuck
Feroot
HubSpot Marketing Hub
Jira
Jira Work Management
Mode
New Relic
Progress DataDirect
SDF
Secoda
Segment
Stonebranch
Wavo
intermix.io

Integrations Supported

Orchestra
Alex Solutions
Amazon Aurora
Amazon EC2
Amazon Redshift
DataBuck
Feroot
HubSpot Marketing Hub
Jira
Jira Work Management
Mode
New Relic
Progress DataDirect
SDF
Secoda
Segment
Stonebranch
Wavo
intermix.io

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Etleap

Company Location

United States

Company Website

etleap.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/glue

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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