Losant Data Tables are designed for relatively static data sets. Something like a table that maps fault codes to their description and other meta data.
Data Tables are backed by a database optimized “write light” and “read heavy”. This means data tables can be queried at high rates, but you’ll notice scalability issues if you attempt to continually insert or update data.
If you do want to continually insert data into a database, the recommended approach would be to connect to a managed cloud DB on Azure, AWS, or Google.
For Azure, we’ve got a guide for using MSSQL.
For Google BigQuery, we’ve got the built-in GCP: BigQuery Node and a guide on using it as a Warm Storage solution.
For AWS, I’d recommend using the AWS Lambda Node to invoke Lambda functions, which in turn query data from something like AWS RDS.
If the data you’re receiving is time series data and related to a device, then it should be stored on Device Attributes. Behind the scenes, all data reported to a device attribute is stored in a time-series database.