Cloud Evaluations

We’re pleased to announce that the Ajilius evaluation version now includes all cloud data warehouse platforms.

Previously, we restricted evaluations to on-premise databases. This was to simplify the evaluation environment.

Now, we’re finding that more and more customers are moving their entire workload to the cloud, and there is no on-premise database. And as those workloads move, the knowledge sets of evaluators move with them.

In recognition of this shift, we now include all databases – both cloud and on-premise – in our evaluation version. You can now trial Snowflake, Redshift and Azure SQL Data Warehouse alongside favourites like SQL Server, PostgreSQL, MariaDB and Exasol.

Ajilius. Tomorrow’s data warehouse, today.



I saw a great tweet from Snowflake today:

I laughed when I read it, it exactly mirrors the way I feel about Oracle, IBM and Teradata (among others) with their cloudwashing of legacy DW platforms.

We’re cloud-first. Cross-cloud. Multi-cloud. Even hybrid-cloud. We’ve been working with cloud data warehouses since they were born.

Ajilius. CLOUD data warehousing.

Release 2.4.2

This week’s release makes the following changes:

  • New data type “char” for single character columns. Used internally for SCD_FROM column in type-2 slowly changing dimensions.
  • New TRUNCATE option for the command line scheduler, cleans up transient data after loads to minimise storage costs on cloud platforms.
  • PostgreSQL interface on Windows was not always being fed UTF-8 encoded data. Added encoding parameter to byte conversion.
  • Deleting the active data warehouse repository on Windows would sometimes fail. Now triggering call to garbage collector to ensure closed connections are purged from memory.

Registered users will receive an email in the next 1-2 days with download instructions.

Interestingly, the last two items only showed up when we shifted our development platforms from OSX to Windows. Really liking the change – like moving back home after living on the road for a while – but it does show up the quirks of the Windows internals compared to OSX and Linux.

The list is lighter than usual because we’re working hard on new features for Version 3 … stay tuned for updates!


Why Data Warehouse Automation kicks the crap out of SSIS

Here’s a great explanation of how to do incremental loads in SSIS. It uses third-party components from Pragmatic Works, and a combination of hand coding and SSIS tasks.

See how complex it is? How long it takes?

Here’s how to do the same thing in Ajilius:

Simply check the box on the column/s that govern incremental change.

Under the covers we do almost exactly the same tasks as described in the blog post, but the difference is that we do them, not you. You make a decision in the UI, and we instantly generate all the code and logic that implements that decision.

That’s it … a perfect example of why Data Warehouse Automation kicks the crap out of  great ETL tools like SSIS, and why we deliver data warehouses in a fraction of the time spent in those products.

Ajilius. Data warehouses. Faster.