Use Case
Virtualize Data Seamlessly Across Multiple Sources
As data resides across diverse systems, accessing it often requires cumbersome ETL processes or significant infrastructure changes. This complexity delays insights and drives up operational costs, limiting organizations’ ability to make real-time, data-driven decisions.
Timbr’s virtualization engine eliminates the need for data movement or duplication by creating a unified virtual layer over disparate sources. It enables seamless no-JOINs querying and integration of data in its original location, ensuring fast, cost-effective access and empowering agile analytics.
CAPABILITIES – VIRTUALIZATION ENGINE
Timbr’s data virtualization engine joins multiple data sources at scale, so users can conveniently consume distributed/siloed data represented as a single semantic graph that can be queried with short and simple SQL queries.
CAPABILITIES – 4 TIER CACHE
Timbr’s intelligent 4 tier cache manager enables users to manage the cache of mappings, relationships and views to optimize performance and processing costs according to changing workloads.
Challenges
Struggling with Data Silos and Complex ETL Processes?Data often resides across numerous systems and formats, creating silos that limit collaboration and insights. Moving or duplicating data with traditional ETL processes increases complexity, costs, and delays, preventing organizations from leveraging real-time information effectively.
Do Legacy Architectures Hinder Your Data Integration?
Legacy data systems struggle to support the diverse formats and platforms found in today’s environments. The lack of interoperability makes seamless integration and cross-platform analytics nearly impossible, restricting organizations’ ability to achieve a unified data view.
Dealing with Inefficient Data Access?
Traditional methods rely on building custom pipelines or physically relocating data, resulting in high maintenance costs and slow query performance. These approaches are resource-intensive and ill-suited for organizations seeking fast, scalable, and agile analytics
Why Timbr
Fast Access to Meaningful Data Without MovementTimbr’s virtualization engine eliminates the need for ETL processes by allowing data to remain in its original systems. Its semantic layer provides a unified interface for querying and integrating disparate data sources, simplifying access and reducing overhead.
Interoperability Across Systems and Formats
Timbr bridges the gap between legacy and modern systems by creating a virtual layer that integrates data across diverse formats and platforms. This ensures seamless interoperability and enables organizations to extract insights from previously siloed data.
Cost-Effective, Scalable Analytics
Timbr replaces traditional, resource-intensive pipelines with efficient, real-time queries. Its scalable architecture ensures that analytics remain agile and cost-effective, even as data volumes and complexities grow.
Impact
Faster Insights Across the EnterpriseWith Timbr’s virtualized access, teams can query and analyze data instantly, accelerating decision-making and delivering actionable insights without the delays of traditional ETL processes.
Enhanced Collaboration and Data Consistency
By unifying access to diverse data sources, Timbr fosters better collaboration across teams and ensures that all stakeholders work with consistent, accurate information.
Reduced Costs and Operational Overhead
Timbr’s virtualization engine minimizes infrastructure costs by eliminating data movement and reducing pipeline maintenance. Organizations can achieve efficient analytics while leveraging existing resources.
