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What is DataLakeHouse.io?

DataLakeHouse.io's Data Sync feature enables users to effortlessly replicate and synchronize data from various operational systems—whether they are on-premises or cloud-based SaaS—into their preferred destinations, mainly focusing on Cloud Data Warehouses. Designed for marketing teams and applicable to data teams across organizations of all sizes, DLH.io facilitates the creation of unified data repositories, which can include dimensional warehouses, data vaults 2.0, and machine learning applications. The tool supports a wide range of use cases, offering both technical and functional examples such as ELT and ETL processes, Data Warehouses, data pipelines, analytics, AI, and machine learning, along with applications in marketing, sales, retail, fintech, restaurants, manufacturing, and the public sector, among others. With a mission to streamline data orchestration for all organizations, particularly those aiming to adopt or enhance their data-driven strategies, DataLakeHouse.io, also known as DLH.io, empowers hundreds of companies to effectively manage their cloud data warehousing solutions while adapting to evolving business needs. This commitment to versatility and integration makes it an invaluable asset in the modern data landscape.

What is Apache Hudi?

Hudi is a versatile framework designed for the development of streaming data lakes, which seamlessly integrates incremental data pipelines within a self-managing database context, while also catering to lake engines and traditional batch processing methods. This platform maintains a detailed historical timeline that captures all operations performed on the table, allowing for real-time data views and efficient retrieval based on the sequence of arrival. Each Hudi instant is comprised of several critical components that bolster its capabilities. Hudi stands out in executing effective upserts by maintaining a direct link between a specific hoodie key and a file ID through a sophisticated indexing framework. This connection between the record key and the file group or file ID remains intact after the original version of a record is written, ensuring a stable reference point. Essentially, the associated file group contains all iterations of a set of records, enabling effortless management and access to data over its lifespan. This consistent mapping not only boosts performance but also streamlines the overall data management process, making it considerably more efficient. Consequently, Hudi's design provides users with the tools necessary for both immediate data access and long-term data integrity.

Media

Media

Integrations Supported

AWS Marketplace
Alluxio
Apache Doris
Apache Flink
Apache Hive
Auth0
Azure Data Lake
DataHub
Google Cloud BigQuery
HubSpot CRM
Meta Ads
Microsoft Teams
PostgreSQL
QuickBooks Online
SQL Server
Shopify
Snowflake
Xero
Zoom
e6data

Integrations Supported

AWS Marketplace
Alluxio
Apache Doris
Apache Flink
Apache Hive
Auth0
Azure Data Lake
DataHub
Google Cloud BigQuery
HubSpot CRM
Meta Ads
Microsoft Teams
PostgreSQL
QuickBooks Online
SQL Server
Shopify
Snowflake
Xero
Zoom
e6data

API Availability

Has API

API Availability

Has API

Pricing Information

$99
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

DataLakeHouse.io

Date Founded

2019

Company Location

United States

Company Website

datalakehouse.io

Company Facts

Organization Name

Apache Corporation

Date Founded

1954

Company Location

United States

Company Website

hudi.apache.org

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

Data Replication

Asynchronous Data Replication
Automated Data Retention
Continuous Replication
Cross-Platform Replication
Dashboard
Instant Failover
Orchestration
Remote Database Replication
Reporting / Analytics
Simulation / Testing
Synchronous Data Replication

Data Warehouse

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

Categories and Features

Data Warehouse

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

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