With the release of InterSystems IRIS Cloud SQL, we're getting more frequent questions about how to establish secure connections over JDBC and other driver technologies. While we have nice summary and detailed documentation on the driver technologies themselves, our documentation does not go as far to describe individual client tools, such as our personal favourite DBeaver. In this article, we'll describe the steps to create a secure connection from DBeaver to your Cloud SQL deployment.

IRIS and Ensemble are designed to act as an ESB/EAI. This mean they are build to process lots of small messages.

But some times, in real life we have to use them as ETL. The down side is not that they can't do so, but it can take a long time to process millions of row at once.

To improve performance, I have created a new SQLOutboundAdaptor who only works with JDBC.

BatchSqlOutboundAdapter

Extend EnsLib.SQL.OutboundAdapter to add batch batch and fetch support on JDBC connection.

Benchmark

Benchmarks released on Postgres 11.2 with 1 000 000 rows fetched and 100 000 rows inserted on 2 columns.

The Caché System Management Portal includes a robust web-based SQL query tool, but for some applications it’s more convenient to use a dedicated SQL client installed on a user’s PC.

SQuirreL SQL is a well known open source SQL client built in Java, which uses JDBC to connect to a DBMS. As such, we can configure SQuirreL to connect to Caché using the Caché JDBC driver.

Finding Caché’s JDBC driver JAR

The JAR file containing the Caché JDBC driver is installed automatically by the Caché installer when installing a full Caché instance or when installing client components only.

Astronomers’ tools

5 years ago, on December 19, 2013, the ESA launched an orbital telescope called Gaia. Learn more about the Gaia mission on the official website of the European Space Agency or in the article by Vitaly Egorov (Billion pixels for a billion stars).

However, few people know what technology the agency chose for storing and processing the data collected by Gaia. Two years before the launch, in 2011, the developers were considering a number of candidates (see “Astrostatistics and Data Mining” by Luis Manuel Sarro, Laurent Eyer, William O’Mullane, Joris De Ridder, pp. 111-112):

• IBM DB2,
• PostgreSQL,
• Apache Hadoop,
• Apache Cassandra and
• InterSystems Caché (to be more precise, the Caché eXTreme Event Persistence technology).

Comparing the technologies side-by-side produced the following results (source):

The first four will probably sound familiar even to schoolchildren. But what is Caché XEP?

Hi, I hope this post helps.

The bottom line: MAXLEN is relevant mostly for odbc/jdbc connections and you need to specify an appropriate value within your  tables (classes), otherwise the data might be truncated when you query it, or even fail when you try to insert data.

GmOwl is a solution that offers an organized and engaging learning platform. It was developed to cater to the increasing need, for learning tools providing a versatile quiz environment that meets users requirements.

The main objective of GmOwl is to deliver an user experience for individuals participating in quizzes while giving administrators comprehensive control, over content and user engagement.

GmOwl uses Java EE with MVC template, and the InterSystems IRIS database is used to store data. The InterSystems JDBC Driver is used to connect to the database.

Due to MySQL's interpretation of SCHEMA differing from the common SQL understanding (as seen in IRIS/SQL Server/Oracle), our automated Linked Table Wizard may encounter errors when attempting to retrieve metadata information to build the Linked Table.

(This also applies to Linked Procedures and Views)

When attempting to create a Linked Table through the Wizard, you will encounter an error that looks something like this:

ERROR #5535: SQL Gateway catalog table error in 'SQLPrimaryKeys'. Error: ' SQLState: (HY000) NativeError: [0] Message: [MySQL][ODBC 8.3(a) Driver][mysqld-5.5.5-10.4.

SSH framework is a relatively representative framework of Java, which was popular many years ago. There are Struts+Spring+hibernate and Spring MVC+Spring+hibernate. Of course, I used the second one in college. If I can connect IRIS to Hibernate as a library, does it also mean that IRIS can be developed using SSH framework in theory?

Tools and environment

JDK 1.8

       Maven

       Hibernate 5.X.X

       IRISHealth-2022.1.3

       intellij idea

       Windows 10 64

Create database

       Create several tables in code mode

Class BKIP.SOA.MonitorScreen.CacheTable.

Intro

In a fast-paced digital era, effective communication is crucial. This article introduces a Java-based chat project, combining the strength of IRIS database and ChatGPT intelligence. Built on Java, it goes beyond real-time messaging, leveraging IRIS and ChatGPT for an enhanced chat experience. Also, the name of the project references the cultural classic - Star Wars.

Building Application

Building our dynamic chat application involves a seamless integration of key components and technologies. Java serves as the heart that drives server-side logic and business operations.

As a former JAVA developer it has always been a challenge to decide which database was the most suitable for the project we were going to develop, one of the main criteria I used was their performance, as well as their HA configuration capabilities ( high availability). Well, now is the time to put IRIS to the test with respect to some of the most commonly used databases, so I've decided to create a small Java project based on SpringBoot that connects via JDBC with a MySQL database, another of PostgreSQL and finally with IRIS.

Apache Spark has rapidly become one of the most exciting technologies for big data analytics and machine learning. Spark is a general data processing engine created for use in clustered computing environments. Its heart is the Resilient Distributed Dataset (RDD) which represents a distributed, fault tolerant, collection of data that can be operated on in parallel across the nodes of a cluster. Spark is implemented using a combination of Java and Scala and so comes as a library that can run on any JVM.

WIN SQL is the normal editor used by most of the users .But we can't download large amount of data using winsql . So I have written a tutorial how to connect with a new Java based editor called Squirrel SQL which can easily download or export data in excel or any other formats. Also I included a Java JCBC connection program to connect with the IRIS database especially a mirroring/failover server.

The last days I've work with the great new feature: LOAD DATA With this post I would like to share my first experiences with you. The following points do not contain any order or other evaluation. These are only things that I noticed when using the LOAD DATA command. It should also be noted that these points are based on the IRIS Version 2021.2.0.617 which is a preview release. So it may be that my observations do not apply to newer IRIS versions. But maybe they are helpful for others.

1) The file path is on server side

I have done my first tests via JDBC.

Introduction

Managing databases and performing CRUD operations are fundamental tasks for developers building data-driven applications. While many database management systems (DBMS) exist, they can be complex and cumbersome to interact with, especially when it comes to creating databases and tables, handling constraints, and performing real-time data operations through an API.

This web-based Database Management Tool simplifies the entire process, offering an intuitive UI for managing databases and tables, alongside a powerful REST API for interacting with the data.

Hi! I've extended my demo repository, andreas5588/demo-dbs-iris, to make it easy to test the FOREIGN SERVER and FOREIGN TABLE features in IRIS.

To achieve this, I created a namespace called FEDERATION. The idea is as follows:

1. Set up JDBC connections for each namespace.
2. Create a FOREIGN SERVER within the FEDERATION namespace for each connection.
3. Define a FOREIGN TABLE a least for one table based on each foreign server.

The Script:  demo-dbs-iris/src/sql/02_create_foreign_server.sql

IRIS does not support executing SQL statements that combine tables from different namespaces.

Keyword: Pandas DataFrame, IRIS, Python, JDBC

Purpose

Pandas DataFrame is popular tool for EDA (Exploratory Data Analysis). In ML tasks, the first thing we usually perform is to understand the data a bit more. Last week I was trying this Covid19 dataset in Kaggle Basically the data is a spreadsheet of 1925 encounter rows with 231 columns, and the task is simply to predict whether a patient (linked to  1 or more encounter records) would be admitted to ICU. So it's a normal classification task, and we would as usual use padas.DataFrame to take a quick look first.

In this article, we will establish an encrypted JDBC connection between Tableau Desktop and InterSystems IRIS database using a JDBC driver. While documentation on configuring TLS with Java clients covers all possible topics on establishing an encrypted JDBC connection, configuring it with Tableau might be a little bit tricky, so I decided to write it down.

Securing SuperServer

Before we start with client connections, you need to configure SuperServer, which by default runs on port 1972 and is responsible for xDBC traffic to accept encrypted connections.

Production Configuration

This demo has an interoperability production with 16 items. 

Production Configuration HL7 + Kafka Producer

The first part of this demonstration consists of sending an HL7 SIU file which will be transmitted to the 2 other HL7 flows (HTTP and TCP), and transformed and transmitted to the Kafka server. HTTP and TCP flows will transform HL7 messages in the same way before sending them to Kafka as well.

When using standard SQL or the object layer in InterSystems IRIS, metadata consistency is usually maintained through built-in validation and type enforcement. However, legacy systems that bypass these layers—directly accessing globals—can introduce subtle and serious inconsistencies.

Understanding how drivers behave in these edge cases is crucial for diagnosing legacy data issues and ensuring application reliability.
The DATATYPE_SAMPLE database is designed to help analyze error scenarios where column values do not conform to the data types or constraints defined in the metadata.

Introduction

This article aims to explore how the FHIR-PEX system operates and was developed, leveraging the capabilities of InterSystems IRIS.

Streamlining the identification and processing of medical examinations in clinical diagnostic centers, our system aims to enhance the efficiency and accuracy of healthcare workflows. By integrating FHIR standards with InterSystems IRIS database Java-PEX, the system help healthcare professionals with validation and routing capabilities, ultimately contributing to improved decision-making and patient care.

This is a sample Ensemble/Health Connect production which demonstrates how to receive an HL7 order (ORM) inbound from a file, extract fields (in this case, basic demographic information), and insert those into a table in an external SQL database via ODBC.  

Included in the zip file:

• Exported code
• Sample ORM message
• 'How to configure' doc 

I've asked a lot of questions leading up to this, so I wanted to share some of my progress.

The blue line represents the number of messages processed.  The background color represents the average response time.  You can see ticks for each hour (and bigger ticks for each day).   Hovering over any point in the graph will show you the numbers for that period in time.

This is super useful for "at a glance" performance monitoring as well as establishing patterns in our utilization.

Here is the query used:

SELECT
    mh.name                                  AS MessageType,
    COUNT(mh.

I just wrote up a quick sample to help a colleague load data into IRIS from R using RJDBC, and figured it's worth sharing here for future reference.

Ultimately it was pretty simple, aside from IRIS not liking "." in column names; the workaround is to just rename the columns. Someone better at R than me could probably provide some generic approach. 

# Need a valid value for JAVA_HOME prior to calling library(RJDBC)
Sys.setenv(JAVA_HOME="C:\\Java\\jdk-8.0.322.

Hi,

I was struggling with a procedure that was meant to receive a string and use it as a filter, I've found that since I want the procedure to do some data transformation and return a dataset, I needed to use objectScript language.

What comes to the data platform (not the user facing application) most of the the events of interest/required are available as predefined system audit events in audit log - out of the box. They just need to be enabled.

As we all know, Caché is a great database that accomplishes lots of tasks within itself. However, what do you do when you need to access an external database? One way is to use the Caché SQL Gateway via JDBC. In this article, my goal is to answer the following questions to help you familiarize yourself with the technology and debug some common problems.

Outline

• What are the connection parameters you need to connect to a remote database?
• What is the JDBC Gateway vs the Java Gateway Service in Ensemble?
• What tools and methods are available to debug issues?

Introduction

There are many entities in IRIS which are extremely difficult to transfer to another system.They usually contain important system-stored objects: users, roles, privileges, mappings, and applications. The exception to this list is for resources, which are facilitated by the ability to select and save them from the management portal interface [System > Security Management > Resources] Yet, things are not as good with other system objects.

In the previous article, we talked about ODBC and connecting from C#. And now, let's look at JDBC and Java. The InterSystems JDBC driver is the recommended, high-performance way to integrate your Java applications.

Here is a step-by-step guide to getting your Java application connected to an IRIS instance using the JDBC driver.

Step 1: Obtain and Include the InterSystems IRIS JDBC Driver

Unlike ODBC drivers, which are often installed system-wide, JDBC drivers are typically distributed as JAR files that must be included in your Java project's classpath.

If InterSystems IRIS is installed on your local machine or another you have access to, you can find the file in install-dir/dev/java/lib/ or similar, where install-dir is the installation directory for the instance. Conversely, you can download the jar file from Driver packages page.

Or as suggested by @Dmitry Maslennikov in the comments, use the maven central repository for Maven:

<dependency>
    <groupId>com.intersystems</groupId>
    <artifactId>intersystems-jdbc</artifactId>
    <version>3.10.5</version>
</dependency>

or for Gradle:

implementation("com.intersystems:intersystems-jdbc:3.10.5")

Include the jar file in Project:

• Maven/Gradle: If you use a build tool, the simplest method is to add the InterSystems JDBC driver as a dependency in your pom.xml or build.gradle file. This automatically downloads and manages the JAR.
• Manual: For simple projects, you must place the JAR file in a project directory (e.g., /lib) and explicitly add it to your classpath when compiling and running.

A Quick Start to InterSystems Cloud SQL Data in Databricks

If you're migrating from Oracle to InterSystems IRIS—like many of my customers—you may run into Oracle-specific SQL patterns that need translation.

Take this example:

SELECT (TO_DATE('2023-05-12','YYYY-MM-DD') - LEVEL + 1) AS gap_date
FROM dual
CONNECT BY LEVEL <= (TO_DATE('2023-05-12','YYYY-MM-DD') - TO_DATE('2023-05-02','YYYY-MM-DD') + 1);

In Oracle:

• LEVEL is a pseudo-column used in hierarchical queries (CONNECT BY). It starts at 1 and increments by 1.
• CONNECT BY LEVEL <= (...)