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Description
The fundamental technology that powers contemporary solutions for data integration and management is designed to swiftly link various structured and unstructured data sources. It allows for the comprehensive cataloging of your entire data environment, ensuring that data remains within its original sources and is retrieved as needed, eliminating the requirement for duplicate copies. Users can construct data models tailored to their needs, even when drawing from multiple data sources, while also concealing the intricacies of back-end systems from end users. The virtual model can be securely accessed and utilized through standard SQL alongside other formats such as REST, SOAP, and OData, promoting easy access to diverse data types. It features complete data integration and modeling capabilities, along with an Active Data Catalog that enables self-service for data and metadata exploration and preparation. Furthermore, it incorporates robust data security and governance measures, ensures rapid and intelligent execution of data queries, and provides real-time data delivery in various formats. The system also supports the establishment of data marketplaces and effectively decouples business applications from data systems, paving the way for more informed, data-driven decision-making strategies. This innovative approach enhances the overall agility and responsiveness of organizations in managing their data assets.
Description
The intelligent semantic layer merges data with its business context and interconnections, consolidates metrics, and speeds up the production of data products by allowing for SQL queries that are 90% shorter. Users can easily model the data using familiar business terminology, creating a shared understanding and aligning the metrics with business objectives. By defining semantic relationships that replace traditional JOIN operations, queries become significantly more straightforward. Hierarchies and classifications are utilized to enhance data comprehension. The system automatically aligns data with the semantic model, enabling the integration of various data sources through a robust distributed SQL engine that supports large-scale querying. Data can be accessed as an interconnected semantic graph, improving performance while reducing computing expenses through an advanced caching engine and materialized views. Users gain from sophisticated query optimization techniques. Additionally, Timbr allows connectivity to a wide range of cloud services, data lakes, data warehouses, databases, and diverse file formats, ensuring a seamless experience with your data sources. When executing a query, Timbr not only optimizes it but also efficiently delegates the task to the backend for improved processing. This comprehensive approach ensures that users can work with their data more effectively and with greater agility.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Google Cloud Platform
Looker
Microsoft Azure
MongoDB
Tableau
Amazon Athena
Amazon Aurora
Apache Drill
Apache Spark
Integrations
Amazon Web Services (AWS)
Google Cloud Platform
Looker
Microsoft Azure
MongoDB
Tableau
Amazon Athena
Amazon Aurora
Apache Drill
Apache Spark
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
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
Denodo Technologies
Founded
1999
Country
United States
Website
www.denodo.com/en
Vendor Details
Company Name
Timbr.ai
Founded
2018
Country
United States
Website
timbr.ai/
Product Features
Data Fabric
Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services