Power Data with Semantic Intelligence
The SQL ontology-based semantic layer integrates data with meaning, relationships, and metrics for streamlined analytics and fast delivery of data products and enterprise apps.
Boost Productivity of Data Teams
Simplify your
Journey from
Data to Knowledge
- Model data using business terms to provide common meaning and align business metrics
- Define sematic relationships that substitute JOINs so queries become much simpler
- Use hierarchies and classifications to better understand data
- Use SQL logic and math operators to filter data and define business rules
- Import industry data models and OWL ontologies to create semantic data models
Semantic Representation
of Data
Semantic Relationships
Hierarchies and Classifications
Business Logic
Semantic Reasoning
Integrate Data
- Automatically map data to the semantic model
- Join multiple data sources with a powerful distributed SQL engine to query data at scale
- Consume data as a connected semantic graph
- Benefit from advanced query optimizations
- Boost performance and save compute costs with an intelligent cache engine and materialized views
Connect Any Data Source
Connect to most clouds, datalakes, data warehouses, databases and any file format. Timbr empowers you to work with your data sources seamlessly.
How you store your data is up to you. By default, nothing is stored in Timbr. When a query is run, Timbr optimizes the query and pushes it down to the backend.
Leverage Universal Consumption of Data
Power Web Apps with Smart REST
- Simplified Data Access: Draw from multiple data sources
- Data Fetching: Request only the fields needed
- Data Nesting: Fetch nested data structures
- Semantic Swagger: Self-documentation (open API spec)
- Relationship Handling: Draw complex relationships in data simplified by the semantic graph
- Reduce Netwok Payload: Enjoy query optimization when data is nested and fetched in a single call
- Security: Role-based and row-level access control
Accelerate Analytics and Insights
Benefit From Short SQL Queries
With JOINs
22 lines of SQL:
With Relationships:
6 lines of SQL
Visually Explore Data as a Graph
- Traverse your relational data across tables and sources
- Generate explorations with SQL or NL queries
- Understand data connections and gain insights
Decouple BI from Data
- Benefit from reusable common metrics and naming conventions across BI tools, scripts, ML models and applications
- Leverage headless BI, replacing static views with dynamically managed concepts and data mappings
- Update the underlying data structure without disrupting end-users and tools
- Push down compute from BI to CDW
- Avoid lock-in of data stores and consumption tools
- Accelerate cloud migration
- Build easier to maintain systems
Easy and Fast
Implementation
- Fully virtual, no ETLs required
- Low code UI or familiar SQL
-
JDBC/ODBC compliant, accessible
to any BI and Data Science tool
Choice of
Deployment Options
- SaaS, cloud or on-premises
- Available on Azure, GCP and AWS
- Containerized in Kubernetes
Tackle your data challenges
smarter and faster
1 GARTNER Cool Vendors in Data Management, June 01, 2021. ID: G00746797. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. The GARTNER COOL VENDOR badge and GARTNER are registered trademarks and services marks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.
