Expressor Software introduces Standard Edition


I wrote a little while ago about expressor’s introduction of a Community Edition and the use of semantic types. While I concentrated in that article on the latter, now that the company is releasing its Standard Edition at the end of February it is worth commenting on the company’s changed approach to marketing.

When expressor was first released it was targeted particularly at Ab Initio and similar high-end implementations, on the basis that its performance was at least as good, it was much easier to use and it was a good deal less expensive. The problem with tackling this end of the market — and this is a general comment that is not specific to expressor — is that lead times tend to be long (and even more so given financial conditions over the last couple of years). This is not what you need as a start-up company.

The introduction of the Community Edition, which is available for free download, represents a significant shift in marketing direction. Instead of competing with high-end vendors all the time (though expressor may continue to do that when appropriate) it means that expressor’s main competitor is likely to be Talend, along with Microsoft SSIS and, of course, hand coding. While expressor is not an open source vendor (though its repository — see below — is based on the open source Subversion standard) its marketing model will now take it directly into competition with Talend.

In so far as the Standard Edition is concerned (there will be an Enterprise Edition in due course) the two main additional features it offers are the repository already referred to and extended engine support.

To start with the latter, the Community Edition comes with an embedded run-time engine but it is single use only, whereas with the Standard Edition a typical configuration might have separate nodes: one for development, one for testing and one for production. In addition, the pipeline parallelism available within the engine is significantly more important for the Standard rather than the Community Edition, because the Community Edition is limited to Windows 7 and XP environments, which tend to be limited to dual core systems. The Standard Edition runs on multi-core Windows Server and Linux machines.

The repository provides what you might expect in terms of version control, check-in and check-out, source control, access to revision history and so on. However, it does not include data lineage and impact analysis: these features will be part of the Enterprise Edition.

There are also a number of enhancements to the product (both editions) as a part of this release. For example, there is now also a facility to create deployment packages by simply dragging and dropping dataflows into them, with all relevant information being automatically included within the package. There are, needless to say, a number of other additional features. The next release (scheduled for April) will remove the product’s current dependency on Microsoft Visio and will also see enhancements to semantic types.

Going beyond the technical, expressor has also implemented a very generous support package (at just $1,150 pa) for users of the Community Edition and, of course, will be targeting users of that version to upgrade them to the Standard Edition.

All in all, this is shaping up like a very sensible strategy. One could wish that the company had chosen this path in the first place but c’est la vie. I expect that expressor will start to make serious inroads at the low end of the market. Its use of semantic types greatly simplifies the development of data integration processes and reduces the number of mappings that have to be performed so that it has a technical advantage and it shouldn’t lose to anyone in performance terms either. Combine that with an open source-like marketing model and expressor should be on to a winner.

Philip Howard is Research Director (Data Management) at Bloor Research. Data management refers to the management, movement, governance and storage of data and involves diverse technologies that include (but are not limited to) databases and data warehousing, data integration (including ETL, data migration and data federation), data quality, master data management, metadata management and log and event management. Philip also tracks spreadsheet management and complex event processing.