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What is lakeFS?

lakeFS enables you to manage your data lake in a manner akin to source code management, promoting parallel experimentation pipelines alongside continuous integration and deployment for your data workflows. This innovative platform enhances the efficiency of engineers, data scientists, and analysts who are at the forefront of data-driven innovation. As an open-source tool, lakeFS significantly boosts the robustness and organization of data lakes built on object storage systems. With lakeFS, users can carry out dependable, atomic, and version-controlled actions on their data lakes, ranging from complex ETL workflows to sophisticated data science and analytics initiatives. It supports leading cloud storage providers such as AWS S3, Azure Blob Storage, and Google Cloud Storage (GCS), ensuring versatile compatibility. Moreover, lakeFS integrates smoothly with numerous contemporary data frameworks like Spark, Hive, AWS Athena, and Presto, facilitated by its API that aligns with S3. The platform's Git-like framework for branching and committing allows it to scale efficiently, accommodating vast amounts of data while utilizing the storage potential of S3, GCS, or Azure Blob. Additionally, lakeFS enhances team collaboration by enabling multiple users to simultaneously access and manipulate the same dataset without risk of conflict, thereby positioning itself as an essential resource for organizations that prioritize data-driven decision-making. This collaborative feature not only increases productivity but also fosters a culture of innovation within teams.

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.

Media

Media

Integrations Supported

AWS IoT SiteWise
Amazon Kinesis
Amazon S3
Amazon SES
Amazon Web Services (AWS)
Apache Kafka
Google Cloud Storage
Jira
Jira Work Management
Localytics
Looker
MLflow
Marketo
Mixpanel
NetSuite
Presto
Salesforce
Segment
SimpleKPI
intermix.io

Integrations Supported

AWS IoT SiteWise
Amazon Kinesis
Amazon S3
Amazon SES
Amazon Web Services (AWS)
Apache Kafka
Google Cloud Storage
Jira
Jira Work Management
Localytics
Looker
MLflow
Marketo
Mixpanel
NetSuite
Presto
Salesforce
Segment
SimpleKPI
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

Treeverse

Date Founded

2020

Company Location

Israel

Company Website

lakefs.io

Company Facts

Organization Name

Etleap

Company Location

United States

Company Website

etleap.com

Categories and Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

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

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