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features
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support

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Description

Traditional Data Lakes frequently simplify their role to merely serving as inexpensive raw data repositories, overlooking crucial elements such as data transformation, quality assurance, and security protocols. Consequently, data scientists often find themselves dedicating as much as 80% of their time to the processes of data acquisition, comprehension, and cleansing, which delays their ability to leverage their primary skills effectively. Furthermore, the establishment of traditional Data Lakes tends to occur in isolation by various departments, each utilizing different standards and tools, complicating the implementation of cohesive analytical initiatives. In contrast, Smart Data Lakes address these challenges by offering both architectural and methodological frameworks, alongside a robust toolset designed to create a high-quality data infrastructure. Essential to any contemporary analytics platform, Smart Data Lakes facilitate seamless integration with popular Data Science tools and open-source technologies, including those used for artificial intelligence and machine learning applications. Their cost-effective and scalable storage solutions accommodate a wide range of data types, including unstructured data and intricate data models, thereby enhancing overall analytical capabilities. This adaptability not only streamlines operations but also fosters collaboration across different departments, ultimately leading to more informed decision-making.

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

Amazon S3 Yes 
Apache Kafka Yes 
Apache Spark Yes 
Hadoop Yes 
Amazon Athena No 
Amazon Kinesis No 
Amazon SES No 
Amazon Web Services (AWS) No 
Apache Airflow No 
Apache Flink No 
Azure Blob Storage No 
Databricks No 
Delta Lake No 
Google Cloud Storage No 
Java Yes 
Jupyter Notebook No 
Looker No 
MLflow No 
MinIO No 
SQL Yes 

Integrations

Amazon S3 Yes 
Apache Kafka Yes 
Apache Spark Yes 
Hadoop Yes 
Amazon Athena Yes 
Amazon Kinesis Yes 
Amazon SES Yes 
Amazon Web Services (AWS) Yes 
Apache Airflow Yes 
Apache Flink Yes 
Azure Blob Storage Yes 
Databricks Yes 
Delta Lake Yes 
Google Cloud Storage Yes 
Java No 
Jupyter Notebook Yes 
Looker Yes 
MLflow Yes 
MinIO Yes 
SQL No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

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 No 
Live Training (Online) No 
In Person No 

Types of Training

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

Vendor Details

Company Name

ELCA Group

Founded

1968

Country

Switzerland

Website

www.elca.ch/en/smart-data-lake-builder-efficient-way-lay-foundations-smarter-data-lake

Vendor Details

Company Name

Treeverse

Founded

2020

Country

Israel

Website

lakefs.io

Product Features

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 

Alternatives

Alternatives