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What is Omnata?
Modern data warehouses have reached unprecedented levels of sophistication, yet the techniques for data integration remain outdated. These legacy middleware systems create substantial challenges for organizations striving for operational agility. By implementing SQL functions within Snowflake, companies can seamlessly transmit data to their applications. Furthermore, it's vital to manage integration in conjunction with other processes within the data pipeline. Reducing the reliance on complex data infrastructures can mitigate security risks and lessen the demands for vendor assurances. The presence of convoluted middleware and ETL frameworks often leads to delays in deployment. It is crucial to preserve agility while also simplifying code complexity. Tackling the challenges associated with consolidating customer data is essential for creating a dependable single source of truth. Recent innovations provide remarkable connectivity and flexibility. Integrations can now function without intermediary systems between the data source and its endpoint. Instead of merely transferring data, Connect leverages live queries to deliver real-time information directly within the destination application, ensuring that users consistently access the latest data. This approach not only improves efficiency but also enhances the overall user experience by providing immediate insights.
What is Data Virtuality?
Unify and streamline your data operations. Transform your data ecosystem into a dynamic force. Data Virtuality serves as an integration platform that ensures immediate access to data, centralizes information, and enforces data governance. The Logical Data Warehouse merges both materialization and virtualization techniques to deliver optimal performance. To achieve high-quality data, effective governance, and swift market readiness, establish a single source of truth by layering virtual components over your current data setup, whether it's hosted on-premises or in the cloud. Data Virtuality provides three distinct modules: Pipes Professional, Pipes Professional, and Logical Data Warehouse, which collectively can reduce development time by as much as 80%. With the ability to access any data in mere seconds and automate workflows through SQL, the platform enhances efficiency. Additionally, Rapid BI Prototyping accelerates your time to market significantly. Consistent, accurate, and complete data relies heavily on maintaining high data quality, while utilizing metadata repositories can enhance your master data management practices. This comprehensive approach ensures your organization remains agile and responsive in a fast-paced data environment.
Integrations Supported
Google Cloud BigQuery
Salesforce
Snowflake
Zendesk
Airship
Amazon Web Services (AWS)
Apache Hive
Google Analytics
Google Sheets
InterSystems Caché
Integrations Supported
Google Cloud BigQuery
Salesforce
Snowflake
Zendesk
Airship
Amazon Web Services (AWS)
Apache Hive
Google Analytics
Google Sheets
InterSystems Caché
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
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
Omnata
Company Location
Australia
Company Website
omnata.com
Company Facts
Organization Name
Data Virtuality
Date Founded
2012
Company Location
Germany
Company Website
datavirtuality.com
Categories and Features
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
Categories and Features
Data Extraction
Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services