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Description
Cloudera Data Warehouse is a cloud-native, self-service analytics platform designed to empower IT departments to quickly provide query functionalities to BI analysts, allowing users to transition from no query capabilities to active querying within minutes. It accommodates all forms of data, including structured, semi-structured, unstructured, real-time, and batch data, and it scales efficiently from gigabytes to petabytes based on demand. This solution is seamlessly integrated with various services, including streaming, data engineering, and AI, while maintaining a cohesive framework for security, governance, and metadata across private, public, or hybrid cloud environments. Each virtual warehouse, whether a data warehouse or mart, is autonomously configured and optimized, ensuring that different workloads remain independent and do not disrupt one another. Cloudera utilizes a range of open-source engines, such as Hive, Impala, Kudu, and Druid, along with tools like Hue, to facilitate diverse analytical tasks, which span from creating dashboards and conducting operational analytics to engaging in research and exploration of extensive event or time-series data. This comprehensive approach not only enhances data accessibility but also significantly improves the efficiency of data analysis across various sectors.
Description
Google Cloud Lakehouse is a modern data storage and management solution that combines the capabilities of data warehouses and data lakes into a unified platform. It enables organizations to store, access, and analyze data in open formats like Apache Iceberg, Parquet, and ORC without duplication. By maintaining a single source of truth, the platform eliminates the need for complex data movement and reduces operational overhead. It offers fine-grained security controls, allowing organizations to manage access and governance policies effectively. The Lakehouse runtime catalog provides centralized metadata management and simplifies resource organization. The platform supports scalable analytics and integrates seamlessly with tools like Apache Spark for advanced data processing. It is designed to handle large-scale data workloads while maintaining high performance and reliability. Built-in best practices and guides help users optimize their data architecture. It also supports replication and disaster recovery for enhanced resilience. Overall, Google Cloud Lakehouse provides a flexible and efficient way to unify and analyze enterprise data.
API Access
Has API
API Access
Has API
Integrations
Amazon S3
Amazon Web Services (AWS)
Apache Druid
Apache Hive
Apache Iceberg
Apache Impala
Apache Kudu
Apache Spark
Azure Data Lake
Google Cloud BigQuery
Integrations
Amazon S3
Amazon Web Services (AWS)
Apache Druid
Apache Hive
Apache Iceberg
Apache Impala
Apache Kudu
Apache Spark
Azure Data Lake
Google Cloud BigQuery
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$5 per TB
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
Cloudera
Founded
2008
Country
United States
Website
www.cloudera.com/products/data-warehouse.html
Vendor Details
Company Name
Founded
1998
Country
United States
Website
docs.cloud.google.com/lakehouse/docs
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 Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge