Possible SQL statement in InlineQuerier:

select i.*, r.*
from "InputData" i, "Ranges" r
where i."sys_time" >= r."low" and i."sys_time" < r."high"

I'm not sure about the speed with your data set though.

@gcarmich​ SQLite support a BETWEEN operator that might simplify your query in the InlineQuerier. If you include a small sample dataset someonemight be able to illustrate the query

Mark, Geomancer did submit an SQL InlineQuerier solution and it worked for my needs. It just took me a while to understand the syntax. I have a workflow with the InlineQuerier and numeric values that work and the Feature Value which does not. I'll post the solution and the files here for future reference:

Unfortunately, the BETWEEN operator is always inclusive: it tests for greater than or equal to the lower value, and less than or equal to the higher value.

In this case an exclusive range was needed, so the greater than (>) and less than operators (<) have to be used.

Hi @gcarmich​, good to see you could use the InlineQuerier, and that it is fast enough for your data.

@gcarmich​ @geomancer​ Just a quick FYI note on performance in the InlineQuerier . 

FME creates an fme_feature_content attribute that contains the entire feature on the input (i.e. all the input attributes) . 

In the Columns section of the Inputs: only include the attributes that you'll explicitly use in your SQL queries  (see the section Configuration -  Inputs of the InLineQueir docs). So, in the example below,  if you're creating a simple JOIN using RECORDID, remove all the other attributes. They'll be preserved in the fme_feature_content and you'll have a much lighter SQLite in memory database.  

and your SQL might look something like:

SELECT "CellTower".*, "CellTowerDetail",* FROM "CellTower"
INNER JOIN "CellTowerDetail" 
ON "CellTower"."RECORDID" = "CellTowerDetail"."RECORDID";

In your example above, you'd have to include the "sys_time" , low" and "high" in the Columns

Why clean-up Columns...?

• You're creating tables that contain many more attributes than you need which will take longer to load and create a larger in memory SQLite database than you need
• All Columns attributes are indexed.  So for larger data datasets with many attributes that's a lot of indexing 

Thank you @Mark Stoakes​, very interesting, I didn't know this. This can really speed up the InlineQuerier.

I learned something new today, and its only 7:25 AM 😁