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Average Ratings 0 Ratings

Total
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features
design
support

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Write a Review

Description

Etleap was created on AWS to support Redshift, snowflake and S3/Glue data warehouses and data lakes. Their solution simplifies and automates ETL through fully-managed ETL as-a-service. Etleap's data wrangler allows users to control how data is transformed for analysis without having to write any code. Etleap monitors and maintains data pipes for availability and completeness. This eliminates the need for constant maintenance and centralizes data sourced from 50+ sources and silos into your database warehouse or data lake.

Description

lakeFS allows you to control your data lake similarly to how you manage your source code, facilitating parallel pipelines for experimentation as well as continuous integration and deployment for your data. This platform streamlines the workflows of engineers, data scientists, and analysts who are driving innovation through data. As an open-source solution, lakeFS enhances the resilience and manageability of object-storage-based data lakes. With lakeFS, you can execute reliable, atomic, and versioned operations on your data lake, encompassing everything from intricate ETL processes to advanced data science and analytics tasks. It is compatible with major cloud storage options, including AWS S3, Azure Blob Storage, and Google Cloud Storage (GCS). Furthermore, lakeFS seamlessly integrates with a variety of modern data frameworks such as Spark, Hive, AWS Athena, and Presto, thanks to its API compatibility with S3. The platform features a Git-like model for branching and committing that can efficiently scale to handle exabytes of data while leveraging the storage capabilities of S3, GCS, or Azure Blob. In addition, lakeFS empowers teams to collaborate more effectively by allowing multiple users to work on the same dataset without conflicts, making it an invaluable tool for data-driven organizations.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS IoT SiteWise Yes 
Amazon Kinesis No 
Amazon Web Services (AWS) No 
Apache Airflow No 
Apache Flink No 
Astro by Astronomer No 
Databricks No 
Delta Lake No 
Google Analytics Yes 
Google Cloud Storage No 
Jira Yes 
Jira Work Management Yes 
Looker No 
MLflow No 
MinIO No 
Mode Yes 
NetSuite Yes 
Orchestra Yes 
Presto No 
Zendesk Yes 

Integrations

AWS IoT SiteWise No 
Amazon Kinesis Yes 
Amazon Web Services (AWS) Yes 
Apache Airflow Yes 
Apache Flink Yes 
Astro by Astronomer Yes 
Databricks Yes 
Delta Lake Yes 
Google Analytics No 
Google Cloud Storage Yes 
Jira No 
Jira Work Management No 
Looker Yes 
MLflow Yes 
MinIO Yes 
Mode No 
NetSuite No 
Orchestra No 
Presto Yes 
Zendesk No 

Pricing Details

Because each company's ETL needs are different, Etleap's pricing is based on the number of sources types you want to integrate with, rather than data usage. We're committed to providing sophisticated, user-friendly ETL-as-a-service regardless of the size of your business.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Etleap

Country

United States

Website

etleap.com

Vendor Details

Company Name

Treeverse

Founded

2020

Country

Israel

Website

lakefs.io

Product Features

Big Data

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

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Product Features

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration No 
Data Migration No 
Data Quality Control No 
Data Security No 
Information Governance No 
Master Data Management No 
Match & Merge No 

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