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What is IBM Db2 Warehouse?

IBM® Db2® Warehouse offers a preconfigured, client-managed data warehouse solution that operates seamlessly in private clouds, virtual private clouds, and various containerized settings. Designed to be an ideal hybrid cloud solution, it empowers users to maintain control over their data while enjoying the advantages of cloud flexibility. The platform incorporates integrated machine learning, automatic scaling, built-in analytics, and supports both SMP and MPP processing capabilities, allowing organizations to implement AI solutions more rapidly and easily. You can establish a pre-configured data warehouse within minutes on your preferred supported infrastructure, with elastic scaling that supports smooth updates and upgrades. By utilizing in-database analytics right where the data resides, companies can enhance their AI capabilities, resulting in faster and more efficient operations. Additionally, the ability to create your application once means you can shift workloads to the most appropriate environment—whether that's a public cloud, private cloud, or on-premises—while making minimal or no changes. This adaptability is crucial for businesses aiming to optimize their data strategies across a variety of deployment choices, ensuring they remain competitive in an ever-evolving market landscape. Furthermore, the user-friendly setup process and robust features make it an appealing option for organizations looking to harness the power of their data effectively.

What is Dimodelo?

Focus on crafting meaningful and influential reports and analytics instead of getting overwhelmed by the intricacies of data warehouse coding. It's essential to prevent your data warehouse from devolving into a disorganized collection of numerous challenging pipelines, notebooks, stored procedures, tables, and views. Dimodelo DW Studio significantly reduces the effort required for the design, construction, deployment, and management of a data warehouse. It supports the creation and implementation of a data warehouse tailored for Azure Synapse Analytics. By establishing a best practice architecture that integrates Azure Data Lake, Polybase, and Azure Synapse Analytics, Dimodelo Data Warehouse Studio guarantees the provision of a high-performing and modern cloud data warehouse. Additionally, the use of parallel bulk loads and in-memory tables further enhances the efficiency of Dimodelo Data Warehouse Studio, allowing teams to prioritize extracting valuable insights over handling maintenance tasks. This shift not only streamlines operations but also empowers organizations to make data-driven decisions with greater agility.

Media

Media

Integrations Supported

Azure Data Lake
Azure DevOps Projects
Azure SQL Database
Azure Synapse Analytics
Microsoft Azure
Microsoft Power BI
SQL Server

Integrations Supported

Azure Data Lake
Azure DevOps Projects
Azure SQL Database
Azure Synapse Analytics
Microsoft Azure
Microsoft Power BI
SQL Server

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$899 per month
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

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/db2-warehouse

Company Facts

Organization Name

Dimodelo

Company Location

Australia

Company Website

www.dimodelo.com

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 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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