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What is Google Cloud Lakehouse?

Google Cloud Lakehouse is an advanced data platform that unifies data warehouses and data lakes into a single, integrated storage and analytics solution. It enables organizations to work with open data formats such as Apache Iceberg, Parquet, and ORC, ensuring flexibility and interoperability across systems. By allowing access to a single copy of data, it eliminates the need for duplication and complex data pipelines. The platform includes a centralized runtime catalog for managing metadata, resources, and access controls efficiently. It provides fine-grained security through IAM roles and table-level permissions, ensuring strong governance and compliance. Google Cloud Lakehouse supports scalable data processing and integrates with tools like Apache Spark for advanced analytics and machine learning workflows. It is designed to handle large volumes of data while maintaining performance and reliability. The platform includes features for replication and disaster recovery, helping ensure data availability and resilience. Comprehensive documentation, guides, and training resources make it easier for teams to get started and optimize their workflows. It also simplifies the management of Iceberg tables and other data structures. The system supports modern data architectures, enabling seamless integration with other Google Cloud services. By unifying storage and analytics, it reduces operational complexity and improves efficiency. Overall, Google Cloud Lakehouse empowers organizations to manage, analyze, and scale their data more effectively in a single platform.

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.

Media

Media

Integrations Supported

Google Cloud BigQuery
Amazon S3
Apache Iceberg
Apache Spark
Azure Data Lake
ConnectWise RMM
Dayforce
Facebook Ads
HubSpot CRM
HubSpot Customer Platform
Microsoft Teams
NetSuite
NetSuite CRM
Presto
Shift4
Stripe
Toast POS
Xero
Zoom

Integrations Supported

Google Cloud BigQuery
Amazon S3
Apache Iceberg
Apache Spark
Azure Data Lake
ConnectWise RMM
Dayforce
Facebook Ads
HubSpot CRM
HubSpot Customer Platform
Microsoft Teams
NetSuite
NetSuite CRM
Presto
Shift4
Stripe
Toast POS
Xero
Zoom

API Availability

Has API

API Availability

Has API

Pricing Information

$5 per TB
Free Trial Offered?
Free Version

Pricing Information

$99
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

Google

Date Founded

1998

Company Location

United States

Company Website

docs.cloud.google.com/lakehouse/docs

Company Facts

Organization Name

DataLakeHouse.io

Date Founded

2019

Company Location

United States

Company Website

datalakehouse.io

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

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

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