InterSystems IRIS is a Complete Data Platform InterSystems IRIS gives you everything you need to capture, share, understand, and act upon your organization’s most valuable asset – your data. As a complete platform, InterSystems IRIS eliminates the need to integrate multiple development technologies. Applications require less code, fewer system resources, and less maintenance.
In the previous articles, we learned the basics of using IMAP protocol to handle messages from mailboxes in an e-mail server. That was cool and interesting, but you could take advantage of implementations created by other ones, available in libraries ready to use.
If one of your packages on OEX receives a review you get notified by OEX only on YOUR package. So @Evgeny Shvarov suggested publishing my monthly summary of my reviews here in DC. It reflects my experience with the status I found at the time of my review.
After >40 years writing in-countable lines of code in M*/COS/ISOS (and a bunch of archaic languages) I decided for myself to set a strong signal for the future. We have Embedded Python available (still pre-release)! I just felt it as a sacrilege to ignore this excellent NEW opportunity and stay with the old sermon that I had used for decades.
There are many ways to generate excel files using Intersystems, some of them are ZEN reports, IRIS reports ( Logi reports or formally known as JReports), or we can use third party Java libraries, the possibilities are almost endless.
But, what if you want to create a simple spreadsheet with only Caché ObjectScript? (no third party applications)
In this webinar, we’ll do a quick tour of the new LOAD DATA feature, also chime in on packaging global data or file data with ZPM, and run a data-generation script as part of a method in the zpm install.
As always, our experts will answer the questions on how to develop, build, and deploy datasets using InterSystems IRIS.
For those of you who might be new to IRIS, and even those who have used Cache or IRIS for some time but want to explore beyond its usually-assumed boundaries and practices, you might want to dive into this detailed exploration of the database engine that is at its heart, and discover just what you can really do with it, going way beyond what InterSystems have done with it for you.
The InterSystems IRIS IntegratedML feature is used to get predictions and probabilities using the AutoML technique. The AutoML is a Machine Learning technology used to select the better Machine Learning algorithm/model to predict status, numbers and general results based in the past data (data used to train the AutoML model). You don't need a Data Scientist, because the AutoML it will test the most common Machine Learning algorithms and select the better algorithm to you, based in the data features analysed. See more here, in this article.
I'm "playing" a little bit with IRIS as document database, as it seems really simple to use.
So far, creating a database and inserting documents is fine. Creating a Property so it can be indexed seems very useful and it works well when this property is created at the very beginning. But here my "problem": whenever a new property is added, how can the values be recalculated and inserted, so indices can be correctly updated?
This is the third article in our short series around innovations in IRIS SQL that deliver a more adaptive, high-performance experience for analysts and applications querying relational data on IRIS. It may be the last article in this series for 2021.2, but we have several more enhancements lined up in this area. In this article, we'll dig a little deeper into additional table statistics we're starting to gather in this release: Histograms
This is the second piece in our series on 2021.2 SQL enhancements delivering an adaptive, high-performance SQL experience. In this article, we'll zoom in on the innovations in gathering Table Statistics, which are of course the primary input for the Run Time Plan Choice capability we described in the previous article.
The 2021.2 release of the InterSystems IRIS Data Platform includes many exciting new features for fast, flexible and secure development of your mission-critical applications. Embedded Python definitely takes the limelight (and for good reason!), but in SQL we've also made a massive step forward towards a more adaptive engine that gathers detailed statistical information about your table data and exploits it to deliver the best query plans. In this brief series of articles, we'll take a closer at three elements that are new in 2021.2 and work together towards this goal, starting with Run Time Plan Choice.
It's hard to figure out the right order to talk about these (you can't imagine how often I've reshuffled them in writing this article!) because they fit together in such a nice way. As such, feel free to go on a limb and read these in random order .