What can we help you with?

Botched backfills…can result in huge swaths or duplicates or missing records, especially if you get your partitions wrong.

Janky JSON blobs…happen in high speed development environments where logging schemas change every week or month.

Manual data mistakes…are a fact of life! When humans are entering data, it’s gonna be wrong sometimes.

Truncated tuples…because somebody didn’t expect a string of that length.

Precision paradoxes…true story, all the transactions were perfect dollar amounts. The column was an INTEGER not a DOUBLE. Oops.

Nonstandard naming…some people think it’s San Francisco some people think it’s Frisco. Unfortunately.

Metrics Toro runs SQL queries on your data warehouse to collect metrics about your data. Metrics could be anything from percent of records matching UUID formats, to summary statistics about numeric values, to the correlation of two timestamps.

Suggestions It helps you figure out which metrics to collect by profiling your data and making suggestions. You can manually configure metrics as well.

Time series Toro creates a time series from every metric it collects. Anomaly detection on the time series determines when something about your data looks like a problem or an anomaly.

Alerts Once a time series goes out of bounds, Toro notifies you with Slack and email alerts. You can also use Toro’s APIs to build custom actions when alerts happen, like stopping an Airflow job.

Deployment We’ve gone from “what’s your AWS account ID” to deployed, connected, and tested in a single Zoom call, thanks to templating like Cloud Formation.

Configuration Customers have reported as much as 40% less time spent to set up the same monitoring in Toro that they used to define manually as part of their ETL work.

We provide lot’s of customization with Toro’s included metrics, but when stuff gets really specific, you can still define custom monitoring using SQL.

Notify Slack channels like #analytics or individuals like #egor.

Email individuals like kyle@company.com or entire mailing lists like data-eng@company.com.

Toro is compatible with any SQL based, JDBC compliant database, including: Redshift, BigQuery, Presto, Snowflake, PostgreSQL, MySQL, and SQL Server. We’re adding and testing support for more databases regularly.

On AWS Cloudformation setup takes < 20 mins.
On all other cloud providers Toro deploys quickly with a simple Docker container.

Lots! Toro has a rich set of APIs so you can manage and trigger tests, take actions on failures, and more. Full docs are available during a pilot installation. Contact us to learn more!