Support and Onboarding Information

You can create a semantic data model powered with relationships and connect it to one or more data sources.  The modeled data can be accessed in SQL, Spark, Phyton, Scala, Java and R, or can be consumed with business intelligence tools via ODBC/JDBC, data science tools and web applications via REST. Modeled data can be graphically explored as a network and can also be analyzed with a library of graph algorithms run with simple SQL queries.

Our platform makes it fast and easy to model data, connect with any datastore, and securely share what you’ve built with other users – all in one place.

Data engineers are generally the ones creating the semantic data models. It usually takes an engineer around ten minutes to understand how Timbr works, and another hour for it to feel natural. But anyone who knows SQL can learn to build pretty quickly – many of the most active builders in Timbr today were once non-technical end users!
You can build Timbr data models for any team to use.

With all plans you can connect to: Amazon Athena, Amazon Aurora, Amazon Redshift, Apache Drill, Apache Spark, Clickhouse, Databricks, Google Big Query, Hive, MariaDB, MySQL, Oracle, PostgreSQL, Presto, SAP Hana, Snowflake, SQL Server, Synapse, Trino, Vertica.

With a Business plan you can also connect to: Microsoft Azure Data Lake, Google Cloud Storage, Amazon S3, Mongo DB

Once you build your semantic graph model in Timbr and map it to your data, the model can be accessed in SQL, Spark, Phyton, Scala, Java and R, or can be consumed with business intelligence tools via ODBC/JDBC, data science tools and web applications via REST API. Modeled data can be graphically explored as a network and can also be analyzed with a library of graph algorithms using simple SQL queries.

Business intelligence apps: Power BI, Tableau, Google Data Studio, Domo and any other app with ODBC and JDBC connector.

Data Science: Timbr is natively accessible to Python’s JPype, JayDeBeAPI, and SQL-Alchemy libraries, in Apache Spark, SQL, R, Python, Scala and Java. Seamlessly connect to Jupyter, Apache Zeppelin and Pandas.

It generally takes an engineer around ten minutes to understand the concepts of Timbr, and another few hours to create a basic model. Timbr is very easy to learn and use. You can watch our tutorial videos here.

All of our plans are available as a cloud version of Timbr (we host). The enterprise plan may also be self-hosted in your cloud (you host).

If you have more stringent data requirements, you can deploy Timbr on-premises in your own VPC/VPN. The setup is via Kubernetes and takes only a few minutes. Please contact us to deploy this option.

Timbr offers the kinds of security, reliability and access controls demanded by the most regulated of enterprises, paired with the flexibility, choice, and customization that is required by the most versatile of developers. Security levels depend on the plan you select.

Timbr does not store data, data remains in your database. 

Yes, for Teams, Business and Enterprise subscription plans.

We suggest you start with the Timbr Startup Plan and then upgrade to Teams or Business as needed.

Sure! You can upgrade or downgrade your subscription plan from within your account at any time.

You can pay using your Azure account or your choice of Visa/MasterCard, Bank Transfer, American Express, JCB, PayPal, Discover, and many other options. Your payment is securely processed by our PCI DSS compliant partner. Enterprise plans can be paid with your Azure cloud account or via wire transfer and direct debit/ACH.

You can modify your subscription by accessing your Timbr account. 

In case that you require advice from our team, we will be glad to assist. After you select a plan, you are given the option to add professional services. You can also add professional services by accessing your account.

Data virtualization is not available for Startup and Teams plans. If you contract a Business plan, you may connect your own data virtualization engine (Spark or Databricks). For Enterprise plans we offer our advanced data virtualization engine.

After you select a plan, you are given the option to add graph algorithms to your plan. There are several options, depending on the memory requirements of the graph algorithms that you use. Start with the first option and, if required, increase the memory plan by accessing your account.

Yes, with an enterprise POC plan. Our team will work closely with you to achieve your use case KPIs. Contact us for more information.