For years, Informix has been powering the world’s most critical business applications. Thousands of clients globally trust the reliability of Informix, with its legendary almost zero downtime and low administration required. Many clients have been leveraging its unique features like NoSQL, Pattern Matching, Smart Triggers, Time Series, and in-database analytics capabilities. More recently with the rise of IoT, Informix’s small footprint and “set it and forget it” capability have made it attractive to full-stack IoT solution developers as they embed Informix in millions of devices and sensors.
One of the key features that makes Informix the ideal choice as an IoT database is its built-in support for MQTT protocol. It allows users to publish data to an Informix database directly via MQTT. This article will show the users how to do it and we will be using the informix sample code that is available in the GitHub repository - https://github.com/informix/samples-MQTT-python.
In this post we look at methods to define data marts in the Informix Warehouse Accelerator (IWA). IWA is a software appliance for the Informix database server, using in-memory, columnar data storage for business intelligence applications doing OLAP. For such workloads IWA typically can achieve a query acceleration of 10 - 100 times faster than running the workload within the Informix database server.
This feature was introduced in the Informix 12.10.xC10 fixpack release. It allows you to assign a character string to your CSDK or JDBC client session and identify that character string on the database server. This is useful for environments where same userid runs multiple instances of the same application, and there is a need to distinguish one session from the other.
Hopefully you have an established routine of local backups or cloud backups, and you should be sleeping a little better (when you get a chance to sleep). And like fire-drills or other emergency procedures, you are probably practicing a restore of your backups on another server. You have probably discovered, depending on the size of your data and speed of the system, this restore may take hours. Moving from ontape to onbar helped by enabling parallel backup and restore of your dbspaces, but while backups can happen with the lights on, during a restore, the server won’t be accessible until the restore is complete. You may not be able to afford for your applications to be down that long.
The headline here is that BLOBspace BLOBs can now be compressed. We made additional enhancements to partition BLOB compression and the auto-compress feature in general. Details follow.
After closing a busy year for Informix at HCL, I was invited to attend an event at Bytec - a major Informix distributor. This was a year end dinner at the beautiful Lindau in Bodensee, in Bayern, southwest of Germany.
After the party, my friend, Richard Luft picked me up at the hotel in Lindau to kick off a busy day of meetings in Friedrischafen, then Munich, then Stuttgart, and then back to Lindau. I was wondering if we would be able to cover the distance of 650km (400 miles), plus all the meetings, and lunch and coffee gatherings, and be back at the hotel as he promised in 12 hrs. He just smiled and answered “Autobahn”.
Primary/Mirror Chunk Swapping
This feature allows you to quickly migrate anything from one INFORMIX chunk up to an entire instance from your current set of disks to a newer and (presumably) faster set of disks, with no downtime.
It has been seven intense months for the Informix team since we started this journey with HCL, and it has been like a band on tour which at the same time is creating new releases. We can’t thank enough for so much positive energy in all of our audiences!
The latest fixpack of Informix was released last month and here is a list of all the new functionality and enhancements included in this version.