The Intelligent Semantic Layer to
Model, Integrate, and Consume Data using
Business Terms and Relationships
Timbr delivers x10 faster data engineering and consumption with agile
semantic modeling, relationships, data virtualization, and up to 90% shorter SQL queries
Timbr in 160 secs:
Empower your data like industry leaders do:
Timbr Unleashes the Power of Smart Data
Give business meaning and relationships to data, unify metrics across teams,
integrate data sources, accelerate delivery of data products and power graph analytics
Agile semantic data modeling
- Model data using business concepts and relationships
- Align business metrics and unify naming conventions
- Map and integrate data seamlessly
- Create business rules and KPIs
- Import and export industry models, ER diagrams and OWL ontologies
Data Virtualization and Intelligent Cache
- Distributed SQL query engine to query across data sources at scale
- Consume sources as a connected semantic graph
- State-of-the-art query optimizations
- Boost performance with multi-tier cache
Short SQL queries
Without Timbr: 22 lines of SQL
With Timbr: 6 lines of SQL
- Query the model in SQL to get 360° view of data
- Quickly formulate complex questions
- Debug and maintain queries easily
- Leverage model relationships that replace JOINs
- Simplify recursive queries
Without Timbr: 22 lines of SQL
SELECT `order`.`order_id`, `order_date`,
`home_office_customer`.`customer_name`,
`first_class_shipment`.`shipping_date`,
`fitness_product`.`product_name`
FROM `scdata`.`datacosupplychaindataset_order` as `order`
LEFT JOIN (
SELECT product_id, product_name
FROM `supply_chain_demo`.`product`
WHERE `department` = 'Fitness') as `fitness_product`
ON `order`.`product_id` = `fitness_product`.`product_id`
LEFT JOIN (
SELECT `order_id`, `shipping_date`
FROM `scdata`.`datacosupplychaindataset_shipment`
WHERE `shipping_mode` = 'First Class') as `first_class_shipment`
ON `order`.`order_id` = `first_class_shipment`.`order_id`
LEFT JOIN (
SELECT `customer_id`,
concat(`customer_first_name`, ' ', `customer_last_name`) as `customer_name`
FROM `scdata`.`datacosupplychaindataset_customer`
WHERE `customer_segment` = 'Home Office') as `home_office_customer`
ON `order`.`customer_id` = `home_office_customer`.`customer_id`
WHERE `product_price` * `order_item_quantity` - `order_item_discount` > 500
With Timbr: 6 lines of SQL
SELECT order_id, order_date,
`ordered_by[home_office_customer].customer_name`,
`in_shipment[first_class_shipment].shipping_date`,
`includes_product[fitness_product].product_name`
FROM dtimbr.`order`
WHERE revenue > 500
- Query the model
- Quickly answer complex questions
- Write and debug queries easily
- Leverage explicit relationships to eliminate JOINs and UNIONs
- Simplify recursive queries
Visually explore data
as a graph
- Gain insights on relationships and properties across data sources
- Understand data dependencies
- Investigate and explore data to drive decision making
- Find answers using no-code UI or search using business terms
Easy and Fast Implementation
- Only SQL-native Knowledge Graph
- Fully virtual, no ETLs required
- Connect your data sources in minutes
- Low code UI or familiar SQL interface
- JDBC/ODBC compliant, accessible to any BI and Data Science tool
Choose your preferred deployment option
- SaaS, cloud or on-premises
- Containerized in Kubernetes
- Available on Azure, GCP and AWS
Easy and Fast Implementation
- Only SQL-native Knowledge Graph
- Fully virtual, no ETLs required
- Map and harmonize your data sources in minutes
- No code UI or familiar SQL interface
- JDBC/ODBC compliant, accessible to any BI and Data Science tool
Choose your preferred deployment option
- SaaS, cloud or on-premises
- Containerized in Kubernetes
- Available on Azure, GCP and AWS
Gain strategic value from data
x10 faster and with minimum effort
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.
1 GARTNER Cool Vendors in Data Management, June 01, 2021. ID: G00746797.
Analysts: Philip Russom , Ehtisham Zaidi , Jason Medd , Eric Thoo , Robert Thanaraj. 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.
