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As CData has been deprecated/is available for additional fee, we’d like to have a native TimeXtender PostgreSQL data source connector.Our current workaround is using ODBC, but this is not the ideal solution (eg. credentials managed on server side, lots of tweaking to load bulk data etc.).
In the post-CData era, getting data from Salesforce using the Enhanced REST connector is quite painful:set up the Objects call to get the list of tables Salesforce contains, especially custom tables for each table call the describe endpoint in a REST endpoint to get the list of field (and their types) use table flattening to make the output as easy to parse as possible use local file cache to get the output you need use your favourite data-mangling tool to get the list of fields, I went with a regular expression to create what I needed turn your field XML into SOQL make REST endpoints for each table deal with pagination and any other complexity use data type overrides to deal with type scanning shortcomingsIt would be nice if there could be an Enhanced connector that does this for Salesforce, I imagine a large number of implementations need to deal with Salesforce after all. I get that at some point Blueprints could be useful for this, but custom tables and fields and some lacking functionality would still make for a painful process in my opinion. Automating the metadata fetching would be much better.
When we use a lot of objects it is necessary to group them in folders or to have them sorted at least alphabetically. For example to see the folders of External Executables, it is a madness:
Add option in Storage management task to clean the ‘_PK’ tables in the ODX database. I've created a topic a while ago about the ‘_PK’ tables are growing rapidly in terms of disk space. To avoid having bigger ‘_PK’ tables then ‘DATA’ tables in the ODX, it would be great this table can be cleaned. I think the storage management task would be the place to do it. You should be able to set the maximum number of batches that need to be saved in the ‘_PK’ tables.As a reference:
From a governance perspective, we would like all production Power BI report measures to be secured and managed in TimeXtender. At the moment, we sometimes have reports with up to 100 measures, which currently have to be retyped one by one as a measure in TX.Power BI allows measures to be exported as a JSON export, which can then also be converted to Excel.How great would it be if we could import these measures directly using the JSON file from PBI, or alternatively via a generic Excel upload function. This would save a lot of manual work.
Hi,When is Qlik Cloud Deliver endpoint estimated to be released for the classic versions?
It would be nice to be able to copy data between DWH instances. Currently it is not possible to copy tables from DWH instance A to DWH instance B. You can load instance A as a source into ODX/Ingest and then load it to instance B, but for large tables it consumes a lot of time and resources (compressing and decompressing parquet etc).We have two scenarios where this feature would be very useful: Make corporately cleansed data (partially) available into smaller division data warehousesOur customer wants to process and cleanse all data from their main systems in one central place. The result is stored in the corporate DWH. But also divisions have their own, smaller DWH. We would like to push data from the corporate DWH to division DWHs in the same way you can copy data between data areas. Make big data sets available for customers and auditorsWhile we can use semantic models, csv export and REST API to make data available to third parties, it sometimes is just too much data for these methods to transfer it efficiently.
Hi there, working with Query tool would be a lot nicer if the structure was different, perhaps with a “Word wrap” feature. Working with large tables, you have to scroll all the way to the right to find what you are looking for. If the standard view would be one line for each column and even “hold ALT and press up/down arrows to rearrange” functionality… that would be really nice!Best regards,Darri
The idea is to add (an option to) the relation of an endpoint from the root level to nested tables when using a REST data source. Currently the normal behavior doesn't incorporate this relation. Meaning you end up with the right tables from the endpoint, but have no way to relate these tables. The CDATA connector did bring this relation. Working with Qlik it brings the relation and even the option to choose a key generation strategy. This seems like a gap in the functionality of the TX REST connector. Workarounds are available but costly in resources. Full description:When working with REST APIs that have nested endpoints my experience is that a standard setup (without for example table flattening) does not take into account the relation within the nesting hierarchy. In other words, in this way the result is 1 root level table that includes the PK and any number of lower level nested tables that cannot be related back to the main table.From what I know I either have the option to use a unnecessarily complex solution using dynamic values and query from endpoint tables. This is undesirable because in some cases I have to query the full endpoint two times and run up costs or into rate limits. The other option would be to table flatten every single nested table and carry over the PK from the root level. This is undesirable as in the past couple of cases I was querying endpoints that originally didn't need any table flattening. So something that works as easy as filling in the right parameters turns into a tedious XSLT job. Adding this functionality to the TX REST connector would help save time and/or reduce the number of necessary API calls. Even more so, it seems to be standard functionality for some of TXs competitors and other players out in the field. Vilsen, Luuk Bouman
It would be nice to be able to use the parameter functions in PowerShell packages
Hi,it would be nice if we can define a prefix (which should be added to the table name when the table is added from ingest into the prepare layer) - more or less the same as it used to work in V20 with business units.How this could work :- add a new property on the data source : prefix- when adding the table to the prepare instance add the prefix to the table.This would avoid issues when several sources have the same tables.
In the scenario when you set up dynamic values or pagination in a TimeXtender REST Data Source, currently the only way to login to a SQL Server instance is by using a SQL account. There are reasons why it would be preferable to use other forms of authentication such as Windows authentication. One of them being central control and management of accounts and credentials.When connecting to an Ingest SQL database storage the dropdown to select one of several types of authentication is available. Is it possible to add this functionality to the REST Data Source SQL server connection as well?Dynamic values example:Ingest instance option:Hilsen,Luuk Bouman
When switching data source providers in TX Classic (v20), TX Classic should keep table/field selections, business unit lookups/parameters and mappings from the business unit to data warehouses … the metadata is there.This feature is a bit urgent because many customers will choose to switch from CData to built-in/enhanced providers before 5 March 2026.
Recently there have been some improvements with logging on the Ingest service. Some analysis are still hard to do, for instance to measure how long it takes to load a particular table/API endpoint if there are multiple tables within one Transfer Task.Prepare instances have detailled logging per table and per step, including a gantt chart. This way you can easily identify tables/steps with bad performance.Currently it can be quite time-consuming to identify slow tables/steps in an Ingest instance. A more detailled logging per step (data transfer, build parquet etc) with start- and endtimestamps, a gantt chart etc. would be a huge time saver. Please also see
The new inline script feature in Fabric notebooks is great. Inline sits right after data cleansing, just before the data frame gets persisted (append or overwrite, as applicable).But sometimes we need scripts that are executed either before table notebook execution starts or after it has finished. An example of the latter is when something needs to be done on an entire incremental table and not just the delta data frame.This can be achieved for example by dummy tables with inline scripts and a lot of manual object dependencies (to get the execution order right), but that’s an inelegant solution with a high risk of missing required object dependencies.Furthermore, dummy tables count towards the painful Fabric workspace limit of 1000 items.It would be good if we, in addition to the current inline scripts, could also have pre- and post-scripts as wrappers of the main notebook. This would handle object dependencies / execution order and we wouldn’t have dummy assets that count towards the 1000 items limit. The pre- and post-scripts should become part of the main notebook even though the developer most likely won’t benefit much from any notebook context (as opposed to the current inline script feature).
It would be really user friendly if you could move the steps in the hierarchy up and down afterwards and behind the scenes there would be a dynamic sort column that would represent the order that is shown in DE.Then you could let the user control the sorting in DE and it would automatically be like that in the reporting layer. Now I usually create a Sort column and the user has to manually fill in values for each step created to control the order.
It would really time efficient if it would be possible to import a hierarchy. It takes a lot of time to create hierarchies using the current function where you have to create all steps manually and all rows manually, one row at a time.If we can get the hierarchy on a certain format like this and import it
We need a feature in Lakehouse solutions whereby we can easily trigger a full load of an incremental table. At the moment, I go to the Prepare Lakehouse and delete the table in question (just the valid table, not the _X tables).
In order to avoid repetitive code, it would be useful to make code snippets and/or use Instance Variables in PowerShell executables.For instance, in this articleAPI keys are used in PowerShell Executables. If you have multiple scripts using the same key, you want to store them somewhere centrally.
It’s not possible to reorder inline scripts (Prepare Lakehouse) … the last script added stays last.I’m a bit OCD-ish and find it easier to navigate large projects when items/assets are sorted alphabetically 😀Please enable script movement / reordering in the Inline Scripts node (like everywhere else).
Many TimeXtender users find the current way of dealing with data type changes quite unnatural to work with. There are many cases where you want to change the data type in Prepare (separate from the painful way to deal with typing in Ingest).A user's instinct is to change the type of a field through ‘Edit field” but this will lead to errors usually. I.e. changing a string to a datetime. Needing to define a new field with the target type and setting up a transformation on that field is a lot of work. You would expect to be able to define a CAST to deal with this ‘between’ Ingest and Prepare, or between Raw and Valid.My suggestion would be to allow a cast to happen between the raw and valid table. This should both support straight casting, int to varchar or similar, and more complex ones like using (try) convert to change a text field into a date. It would be great if you could set up pattern-based text-to-datetime conversions from the UI instead of needing to write sql. It would also be good to wrap conversions in try and be able to specify a fallback value.One of the main reasons for doing this in Prepare vs. Ingest is that data type conversions are expensive in Ingest and obviously less flexible.
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