Copy (ELT) TMetric data to Databricks in a few clicks and keep it up to date automatically.
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If needed, configure replication settings — exclude certain fields, change table naming, apply data hashing, add filters for data.
Configure scheduling and run replication every month, week or day, at specific time or recurrently at any interval, up to once per minute.
View all the integration runs for any period, get email notifications and detailed per-record error logs in case of errors to help you be aware of the situation.
Many businesses want to benefit from the Databricks ability to quickly perform complex analytical queries over petabytes of data, and need to load their data from TMetric and other applications to the Databricks service for centralized storing and data analysis. Skyvia's Replication is the perfect tool for secure replication to a data warehouse, as it loads data much faster than standard ETL tools and allows you to copy TMetric objects (including TimeEntries, Tasks etc.) to Databricks in just a few clicks and keep this copy up to date.
You don’t need to prepare the Databricks database — Skyvia creates the tables, corresponding to the TMetric objects, in the data warehouse automatically. Besides, it can automatically modify target Databricks tables according to new fields added in TMetric.
With Skyvia you can extract and load all the data from a TMetric object or disable loading for some TMetric object fields. You can also configure filters for data to replicate.
Skyvia allows you to hash sensitive data, like names and emails. You can conceal personally identifiable information for better compliance and preserve analytical value of replicated data at the same time.
Skyvia not just copies TMetric data to Databricks once, it can keep your Databricks database up-to-date with TMetric automatically, ensuring you always have fresh data for data analysis without any user intervention.
History mode allows you to store all versions of TMetric records in your Databricks database instead of keeping only the current versions. You can select the mode for each object separately.
By default, target tables are named in the same way as source objects. Skyvia offers settings that allow you to change target table names — for all TMetric objects in the integration or for each one separately. This is especially useful if you load several TMetric instances into the same Databricks database, and want to use separate tables for them.
Skyvia combines a high-performance optimized batch data loading into Databricks with a granular, per-record data insertion and error logging in case of any errors.
If you need more than just to copy data from TMetric to Databricks, you may use Skyvia's powerful ETL functionality for TMetric and Databricks integration. Skyvia's Import tool will correctly extract TMetric data, transform it, and load to Databricks when Databricks tables have different structure than TMetric objects. Besides, if you ever need to load data back from Databricks to TMetric, Skyvia Import allows loading data in any direction, supporting Reverse ETL scenario.
For more complex cases, you can use Data Flow and Control Flow tools. They are designer-based solutions for creating complex data pipelines, involving not only TMetric and Databricks connectors, but any number of connectors in one integration. With these tools you can automate data workflows, involving custom logic, complex multistage transformations, combine data from different sources, load them into multiple destinations at once and many more.
Use flexible scheduling settings to automate replication
You can find detailed logs for each execution in the Integration Run History.
Enable email notifications and always know if anything goes wrong.
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Integrate TMetric and Databricks data with minimal effort with Skyvia.
