FAQ : DataLakeHouse.io

Here are answers to some common questions users typically have about DataLakeHouse:

No! Follow our simple instructions to guide you and with just a few clicks, you can easily load Data from any Source into Snowflake at the frequency of your choosing, and watch your Data flow 🙂

DataLakeHouse.io currently offers Connectors (aka connections or integrations) for many popular solutce systems, for example:

+ New Sources Added Frequently. You can request a connector anytime if the one you are looking for is not listed.

No. DLH.io focuses on a number of cloud data warehouse and storage technology vendors for you to synchronize and replicate your data. Our Business Critical plan offers both tailored Sources and Targets to meet your organization's needs, if needed. We boast turnaround times of less than four weeks for most connector integrations.

This depends on the Data Source it's coming from, but we currently offer Sync Bridges that bring data in as frequently as every 15 minutes (faster if on our Business Critical plan). Additional intervals offered include every 30 minutes, 1 hour, 2, 3, 6, 8, 12, and 24 hours. Depending on your organization's specific needs, you might want to consider our Business Critical plan, which offers additional synchronization frequencies.

Yes! You can setup Alerts & Notifications for email and Slack that let you know thinks like:

For more information, review Alerts & Notifications

Frequently Asked Questions about DataLakeHouse.io will always be available here. Also, join our Slack community for more insights and to collaborate with other DataLakeHouse users and developers.

DLH.io handles the following types of changes from source systems:

DLH.io does not handle deletions for structural source system metadata. An example is that of if a customer has a source, for example a PostgreSQL database and sychronizes a set of database tables to a target successfully, and then at the source an action is conducted by the customer to delete/drop a colum, DLH.io will not in the next subsequent data load of that table remove the column from the target system. This would be a direct violation of data integrity as DLH.io would be uninformed if the change made was by accident by the customer, temporary, etc.

It might not be obvious to some customers or developers but the downstream impact potential could be severe in a production setting where if DLH.io removed a target column that previously contained data that was used for production reporting or development for exmple in the data warehouse that column and its data would be removed, thus impacting any systems or applications depending on said column or structure. Therefor, customers should take note that if they choose to delete a database source system structure by dropping a column they must themselves handle the target system impact. If a column is dropped in the source system the target column will remain but it will no longer be updated with data by DLH.io as DLH.io understands that that column no longer exists in the source.

DataLakeHouse.io has a number of system generated columns to each table in the Target Connection. Below is the definition of each of these columns:



You can communicate with our support team using our support portal, or by sending us an email. More on support is found here in our Customer Support page.