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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

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.

Description

Fully compatible with Netezza, this solution offers a streamlined command-line upgrade option. It can be deployed on-premises, in the cloud, or through a hybrid model. The IBM® Netezza® Performance Server for IBM Cloud Pak® for Data serves as a sophisticated platform for data warehousing and analytics, catering to both on-premises and cloud environments. With significant improvements in in-database analytics functions, this next-generation Netezza empowers users to engage in data science and machine learning with datasets that can reach petabyte levels. It includes features for detecting failures and ensuring rapid recovery, making it robust for enterprise use. Users can upgrade existing systems using a single command-line interface. The platform allows for querying multiple systems as a cohesive unit. You can select the nearest data center or availability zone, specify the desired compute units and storage capacity, and initiate the setup seamlessly. Furthermore, the IBM® Netezza® Performance Server is accessible on IBM Cloud®, Amazon Web Services (AWS), and Microsoft Azure, and it can also be implemented on a private cloud, all powered by the capabilities of IBM Cloud Pak for Data System. This flexibility enables organizations to tailor the deployment to their specific needs and infrastructure.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon S3 Yes 
3forge No 
Arcion No 
Captain Compliance No 
DBHawk No 
Datametica No 
DbVisualizer No 
Digna No 
IBM Cloud Pak for Data No 
IBM Cognos Analytics No 
IBM watsonx.data No 
IRI Voracity No 
Microsoft 365 No 
Presto Yes 
RazorSQL No 
SAS Federation Server No 
SMART Business Suite No 
SOLIXCloud CDP No 
Style Intelligence No 

Integrations

Amazon S3 Yes 
3forge Yes 
Arcion Yes 
Captain Compliance Yes 
DBHawk Yes 
Datametica Yes 
DbVisualizer Yes 
Digna Yes 
IBM Cloud Pak for Data Yes 
IBM Cognos Analytics Yes 
IBM watsonx.data Yes 
IRI Voracity Yes 
Microsoft 365 Yes 
Presto No 
RazorSQL Yes 
SAS Federation Server Yes 
SMART Business Suite Yes 
SOLIXCloud CDP Yes 
Style Intelligence Yes 

Pricing Details

$5 per TB
Free Trial Yes 
Free Version No 

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 Yes 
Live Training (Online) No 
In Person Yes 

Types of Training

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

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

docs.cloud.google.com/lakehouse/docs

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/netezza

Product Features

Data Warehouse

Ad hoc Query No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

Product Features

Data Warehouse

Ad hoc Query No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

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