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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Hudi serves as a robust platform for constructing streaming data lakes equipped with incremental data pipelines, all while utilizing a self-managing database layer that is finely tuned for lake engines and conventional batch processing. It effectively keeps a timeline of every action taken on the table at various moments, enabling immediate views of the data while also facilitating the efficient retrieval of records in the order they were received. Each Hudi instant is composed of several essential components, allowing for streamlined operations. The platform excels in performing efficient upserts by consistently linking a specific hoodie key to a corresponding file ID through an indexing system. This relationship between record key and file group or file ID remains constant once the initial version of a record is written to a file, ensuring stability in data management. Consequently, the designated file group encompasses all iterations of a collection of records, allowing for seamless data versioning and retrieval. This design enhances both the reliability and efficiency of data operations within the Hudi ecosystem.

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Athena
Apache Flink
Apache Hive
Apache Kafka
Apache Spark
Hadoop
Presto
Actian Data Observability
Amazon Kinesis
Amazon SES
Amazon Web Services (AWS)
Apache Airflow
Apache Cassandra
Azure Data Lake
Google Cloud Storage
MLflow
MinIO
MySQL
Onehouse
SimpleKPI

Integrations

Amazon Athena
Apache Flink
Apache Hive
Apache Kafka
Apache Spark
Hadoop
Presto
Actian Data Observability
Amazon Kinesis
Amazon SES
Amazon Web Services (AWS)
Apache Airflow
Apache Cassandra
Azure Data Lake
Google Cloud Storage
MLflow
MinIO
MySQL
Onehouse
SimpleKPI

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Apache Corporation

Founded

1954

Country

United States

Website

hudi.apache.org

Vendor Details

Company Name

Treeverse

Founded

2020

Country

Israel

Website

lakefs.io

Product Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Product 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

Alternatives

Alternatives

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