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.

Hi experts

I'm trying to configure an IRIS ODBC connection with "Windows NT authentication using the network login ID". I have created the System DSN as below:

and user (PROD\test) in the SQL Gateway connection 

However, as the error message suggests, IRIS is trying to connect with PROD\svc_mist, rather than PROD\test configured above. 

Is there anyway to configure the ODBC connection with specified account with Windows Auth method? 

I was facing the same issue as Jerry faced when connecting IRIS to SQL server. My ODBC connection is configured to authenticate via windows authentication.

Configure IRIS ODBC connection with Windows authentication using a
 

How I fixed it for myself?

Root cause

In this tutorial, I will discuss how can you connect your IRIS data platform to sql server db  .

Prereq: 

• Have ODBC driver installed in your device. You can download it from here: Download ODBC Driver for SQL Server - ODBC Driver for SQL Server | Microsoft Learn. 
• Have SQL Server and IRIS installed in your device
• Have SQL Server connection Authentication enabled in SQL server

We are trying to make an ODBC connection via our intersystems ensemble (2016.2 running on ubuntu). However, when I am testing the connection I receive a pop-up that: "Http object response incomplete or invalid.0,#R". Note that the iodbctrace.log remains empty (and it is working because on the first try it registered a 459 error that I should activate kerberos, which I did). Any advise where I should look?
I have taken the following actions:

1. Expand the cacheodbc.ini in the mgr directory as follows:

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:

Someone, please point me to the location of the cache ODBC drivers, as I only found IRIS ODBC drivers.

Any plans for ODBC 3.8 support?

I have set up an ODBC driver for InterSystems and would like to set up a linked server. This all works except I cannot see the columns  details. If I access the database from excel I can get the columns and types of the various tables

Any help or instructions would be appreciated 

Terry

I am writing this post primarily to gather an informal consensus on how developers are using Python in conjunction with IRIS, so please respond to the poll at the end of this article! In the body of the article, I'll give some background on each choice provided, as well as the advantages for each, but feel free to skim over it and just respond to the poll.

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:

Recently, the question came up while discussing the access to the data stored in IRIS from different languages with my students if it was possible to initiate the connection and get data from Cloud solution (InterSystems IRIS CloudSQL) from Microsoft Excel, not the other way around. Considering the many varied ways one can get data in Excel (import data from external sources, connecting to databases using ODBC drivers, using power queries and web queries etc.) the obvious choice was to try ODBC driver. The only task left was to try to connect to the database in the cloud using the ODBC driver.

Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 3 – REST and Interoperability

Now that we have finished the configuration of the SQL Gateway and we have been able to access the data from the external database via python, and we have set up our vectorized base, we can perform some queries. For this in this part of the article we will use an application developed with CSP, HTML and Javascript that will access an integration in Iris, which then performs the search for data similarity, sends it to LLM and finally returns the generated SQL. The CSP page calls an API in Iris that receives the data to be used in the query, calling the integration. For more information about REST in the Iris see the documentation available at https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cl…

Hello community members!
I am trying to connect to Caché database from Azure data factory using ODBC connection. The aim is to read data from Caché and write it in Azure blob storage using copy activity. The ODBC connection is successful and i can see the Caché  tables, but i'm facing an error while reading the table contents.
I'm getting the below error :

Hello everyone,

How can i download the iris odbc for linux ubuntu in order to recover the file 'libirisodbcu.so'.

thanks in advance

Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 2 – Python and Vector Search

Since we have access to the data from our external table, we can use everything that Iris has to offer with this data. Let's, for example, read the data from our external table and generate a polynomial regression with it.

For more information on using python with Iris, see the documentation available at https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=AFL_epython

Let's now consume the data from the external database to calculate a polynomial regression. To do this, we will use a python code to run a SQL that will read our MySQL table and turn it into a pandas dataframe:

Using SQL Gateway with Python, Vector Search, and Interoperability in InterSystems Iris

Part 1 - SQL Gateway

Hello

In this article we will look at the use of SQL Gateway in Iris. SQL Gateway allows Iris to have access to tables from other (external) database via ODBC or JDBC. We can access Tables or Views from various databases, such as Oracle, PostgreSQL, SQL Server, MySQL and others.

In MySQL I have the following table:

CREATE TABLE `info` (
   `created` int(11)
);

And it is linked (via JDBC SQL Gateway) to Cache table mysql.info.  `created` field stores unix timestamp. So when I execute  this SQL in SMP:

SELECT created FROM mysql.info

I receive the following output (which is expected):

But I want to to display `created` field converted to ODBC timestamp format. To do that I call this SQL procedure

I am currently experiencing frustration with trying to Authenticate an Active Directory account through JDBC as the Hospital System moves from OnPrem SQL Server to using Azure SQL Server with Microsoft Entra Authentication.

Microsoft cannot give me a straight answer of what is required from a JDBC standpoint to authenticate from a Linux environment.

Hi everyone,

I'm trying to connect my Laravel application with the InterSystems IRIS Data Platform using ODBC.I need help setting up the ODBC connection and querying the database properly. What is the proper way to configure Laravel to work with an ODBC connection to InterSystems IRIS?

Any help would be greatly appreciated!

Thanks in advance!

How to create an ODBC connection on your native Windows laptop to IRIS running on a Windows VM on the same computer, test the connection, and pull data from IRIS into Excel.

Recently I learned that Excel can connect to external databases via ODBC. This includes basically any ODBC data source. Since IRIS speaks ODBC via the ODBC API, we can take advantage of the InterSystems ODBC Driver to establish an ODBC connection to IRIS on Windows that Excel can utilize.

I’m trying to connect to an InterSystems Caché database from my local development environment using an IPv4 address. Most examples I’ve found show how to connect using the ODBC driver with the localhost or the default IP address (127.0.0.1). However, I want to know how to connect using my local IPv4 address.

Here’s what I need help with:

In the past, I've created custom SQL operations, but now I had something trivial to do, so I decided to take EnsLib.SQL.Operation.GenericOperation out for a spin. There's no example in the docs, so it was a little tricky. Here's what I ended up doing:

In my external database, I have 'mytable' with two fields 'id1' and 'id2'. Here are the pertinent Business Operation settings:

SQL: select id2 from mytable where id1 = ?
Input Parameters: [1] *id1
RequestClass: Ens.StringRequest
ResponseClass: MyResponseClass

I am experiencing an issue while executing a stored procedure in InterSystems Cache. Here’s the procedure I createdCREATE PROCEDURE Silk.sp_InsertRecord (    IN RecordDate TIMESTAMP,    IN UserName VARCHAR(50),    IN RecordType INT,    IN RecordID VARCHAR(50),    IN CategoryID INT,    IN ApprovalDate TIMESTAMP,    IN FileSize BIGINT,    IN WorkstationName VARCHAR(50))BEGIN     INSERT INTO DummyRecords (        RecordKey,         FilePath,         RecordDate,         UserName,         RecordType,         RecordID,         CategoryID,         FileSize    )     VALUES (       

It has been asked a few times recently, how one can make Laravel Framework work with InterSystems IRIS Data Platform. It's been a while since this post about Laravel and InterSystems Caché was published. To bring it up to date, the article gives a brief instruction set on how to setup and configure a Laravel project for use with InterSystems IRIS through ODBC.

What is Laravel?

Problems with Strings

I am accessing IRIS databases with JDBC (or ODBC) using Python. I want to fetch the data into a pandas dataframe to manipulate the data and create charts from it. I ran into a problem with string handling while using JDBC. This post is to help if anyone else has the same issues. Or, if there is an easier way to solve this, let me know in the comments!

I am using OSX, so I am unsure how unique my problem is. I am using Jupyter Notebooks, although the code would generally be the same if you used any other Python program or framework.

The JDBC problem

When I fetch data from the database the column descriptions and any string data are returned as data type java.lang.String. If you print string data data it will look like: "(p,a,i,n,i,n,t,h,e,r,e,a,r)" instead of the expected "painintherear".

This is probably because character strings of data type java.lang.String are coming through as an iterable or array when fetched using JDBC. This can happen if the Python-Java bridge you're using (e.g., JayDeBeApi, JDBC) is not automatically converting java.lang.String to a Python str in a single step.

Python's str string representation, in contrast, has the whole string as a single unit. When Python retrieves a normal str (e.g. via ODBC), it doesn't split into individual characters.

The JDBC Solution

To fix this issue, you must ensure that the java.lang.String is correctly converted into Python's str type. You can explicitly handle this conversion when processing the fetched data so it is not interpreted as an iterable or list of characters.

There are many ways to do this string manipulation; this is what I did.

import pandas as pd

import pyodbc

import jaydebeapi
import jpype

def my_function(jdbc_used)

    # Some other code to create the connection goes here
    
    cursor.execute(query_string)

    if jdbc_used:
        # Fetch the results, convert java.lang.String in the data to Python str
        # (java.lang.String is returned "(p,a,i,n,i,n,t,h,e,r,e,a,r)" Convert to str type "painintherear"
        results = []
        for row in cursor.fetchall():
            converted_row = [str(item) if isinstance(item, jpype.java.lang.String) else item for item in row]
            results.append(converted_row)

        # Get the column names and ensure they are Python strings 
        column_names = [str(col[0]) for col in cursor.description]

        # Create the dataframe
        df = pd.DataFrame.from_records(results, columns=column_names)
        
        # Check the results
        print(df.head().to_string())
        
    else:  
        # I was also testing ODBC
        # For very large result sets get results in chunks using cursor.fetchmany(). or fetchall()
        results = cursor.fetchall()
        # Get the column names
        column_names = [column[0] for column in cursor.description]
        # Create the dataframe
        df = pd.DataFrame.from_records(results, columns=column_names)

    # Do stuff with your dataframe

The ODBC problem

When using an ODBC connection, strings are not returned or are NA.

If you're connecting to a database that contains Unicode data (e.g., names in different languages) or if your application needs to store or retrieve non-ASCII characters, you must ensure that the data remains correctly encoded when passed between the database and your Python application.

The ODBC solution

This code ensures that string data is encoded and decoded using UTF-8 when sending and retrieving data to the database. It's especially important when dealing with non-ASCII characters or ensuring compatibility with Unicode data.

def create_connection(connection_string, password):
    connection = None

    try:
        # print(f"Connecting to {connection_string}")
        connection = pyodbc.connect(connection_string + ";PWD=" + password)

        # Ensure strings are read correctly
        connection.setdecoding(pyodbc.SQL_CHAR, encoding="utf8")
        connection.setdecoding(pyodbc.SQL_WCHAR, encoding="utf8")
        connection.setencoding(encoding="utf8")

    except pyodbc.Error as e:
        print(f"The error '{e}' occurred")

    return connection

connection.setdecoding(pyodbc.SQL_CHAR, encoding="utf8")

Tells pyodbc how to decode character data from the database when fetching SQL_CHAR types (typically, fixed-length character fields).

connection.setdecoding(pyodbc.SQL_WCHAR, encoding="utf8")

Sets the decoding for SQL_WCHAR, wide-character types (i.e., Unicode strings, such as NVARCHAR or NCHAR in SQL Server).

connection.setencoding(encoding="utf8")

Ensures that any strings or character data sent from Python to the database will be encoded using UTF-8, meaning Python will translate its internal str type (which is Unicode) into UTF-8 bytes when communicating with the database.

Putting it all together

Install JDBC

Install JAVA - use dmg

https://www.oracle.com/middleeast/java/technologies/downloads/#jdk23-mac

Update shell to set default version

$ /usr/libexec/java_home -V
Matching Java Virtual Machines (2):
    23 (arm64) "Oracle Corporation" - "Java SE 23" /Library/Java/JavaVirtualMachines/jdk-23.jdk/Contents/Home
    1.8.421.09 (arm64) "Oracle Corporation" - "Java" /Library/Internet Plug-Ins/JavaAppletPlugin.plugin/Contents/Home
/Library/Java/JavaVirtualMachines/jdk-23.jdk/Contents/Home
$ echo $SHELL
/opt/homebrew/bin/bash
$ vi ~/.bash_profile

Add JAVA_HOME to your path

export JAVA_HOME=$(/usr/libexec/java_home -v 23)
export PATH=$JAVA_HOME/bin:$PATH

Get the JDBC driver

https://intersystems-community.github.io/iris-driver-distribution/

Put the jar file somewhere... I put it in $HOME

$ ls $HOME/*.jar
/Users/myname/intersystems-jdbc-3.8.4.jar

Sample code

It assumes you have set up ODBC (an example for another day, the dog ate my notes...).

Note: this is a hack of my real code. Note the variable names.

import os

import datetime
from datetime import date, time, datetime, timedelta

import pandas as pd
import pyodbc

import jaydebeapi
import jpype

def jdbc_create_connection(jdbc_url, jdbc_username, jdbc_password):

    # Path to JDBC driver
    jdbc_driver_path = '/Users/yourname/intersystems-jdbc-3.8.4.jar'

    # Ensure JAVA_HOME is set
    os.environ['JAVA_HOME']='/Library/Java/JavaVirtualMachines/jdk-23.jdk/Contents/Home'
    os.environ['CLASSPATH'] = jdbc_driver_path

    # Start the JVM (if not already running)
    if not jpype.isJVMStarted():
        jpype.startJVM(jpype.getDefaultJVMPath(), classpath=[jdbc_driver_path])

    # Connect to the database
    connection = None

    try:
        connection = jaydebeapi.connect("com.intersystems.jdbc.IRISDriver",
                                  jdbc_url,
                                  [jdbc_username, jdbc_password],
                                  jdbc_driver_path)
        print("Connection successful")
    except Exception as e:
        print(f"An error occurred: {e}")

    return connection


def odbc_create_connection(connection_string):
    connection = None

    try:
        # print(f"Connecting to {connection_string}")
        connection = pyodbc.connect(connection_string)

        # Ensure strings are read correctly
        connection.setdecoding(pyodbc.SQL_CHAR, encoding="utf8")
        connection.setdecoding(pyodbc.SQL_WCHAR, encoding="utf8")
        connection.setencoding(encoding="utf8")

    except pyodbc.Error as e:
        print(f"The error '{e}' occurred")

    return connection

# Parameters

odbc_driver = "InterSystems ODBC"
odbc_host = "your_host"
odbc_port = "51773"
odbc_namespace = "your_namespace"
odbc_username = "username"
odbc_password = "password"

jdbc_host = "your_host"
jdbc_port = "51773"
jdbc_namespace = "your_namespace"
jdbc_username = "username"
jdbc_password = "password"

# Create connection and create charts

jdbc_used = True

if jdbc_used:
    print("Using JDBC")
    jdbc_url = f"jdbc:IRIS://{jdbc_host}:{jdbc_port}/{jdbc_namespace}?useUnicode=true&characterEncoding=UTF-8"
    connection = jdbc_create_connection(jdbc_url, jdbc_username, jdbc_password)
else:
    print("Using ODBC")
    connection_string = f"Driver={odbc_driver};Host={odbc_host};Port={odbc_port};Database={odbc_namespace};UID={odbc_username};PWD={odbc_password}"
    connection = odbc_create_connection(connection_string)


if connection is None:
    print("Unable to connect to IRIS")
    exit()

cursor = connection.cursor()

site = "SAMPLE"
table_name = "your.TableNAME"

desired_columns = [
    "RunDate",
    "ActiveUsersCount",
    "EpisodeCountEmergency",
    "EpisodeCountInpatient",
    "EpisodeCountOutpatient",
    "EpisodeCountTotal",
    "AppointmentCount",
    "PrintCountTotal",
    "site",
]

# Construct the column selection part of the query
column_selection = ", ".join(desired_columns)

query_string = f"SELECT {column_selection} FROM {table_name} WHERE Site = '{site}'"

print(query_string)
cursor.execute(query_string)

if jdbc_used:
    # Fetch the results
    results = []
    for row in cursor.fetchall():
        converted_row = [str(item) if isinstance(item, jpype.java.lang.String) else item for item in row]
        results.append(converted_row)

    # Get the column names and ensure they are Python strings (java.lang.String is returned "(p,a,i,n,i,n,t,h,e,a,r,s,e)"
    column_names = [str(col[0]) for col in cursor.description]

    # Create the dataframe
    df = pd.DataFrame.from_records(results, columns=column_names)
    print(df.head().to_string())
else:
    # For very large result sets get results in chunks using cursor.fetchmany(). or fetchall()
    results = cursor.fetchall()
    # Get the column names
    column_names = [column[0] for column in cursor.description]
    # Create the dataframe
    df = pd.DataFrame.from_records(results, columns=column_names)

    print(df.head().to_string())

# # Build charts for a site
# cf.build_7_day_rolling_average_chart(site, cursor, jdbc_used)

cursor.close()
connection.close()

# Shutdown the JVM (if you started it)
# jpype.shutdownJVM()

Hello, I need to use IRIS to connect to an MSSQL base.
It has to be done via ODBC, I can't use JDBC at this time by client option.

I am trying to use Microsoft Driver
libmsodbcsql-13.1.so.9.2

But I can't, my attempts result in:
Connection failed.
SQLState: () NativeError: [11001] Message:

I have done all DSN configuration, and my configuration is listed in SQL Gateway Connections. I know it's working, because when I run a test with isql I have the information that connects to the bank.

This is my IRIS and Server configuration:
IRIS for UNIX (Ubuntu Server LTS for x86-64) 2018.1.1 (Build 643U)

Hello community,

How to install the iris  package installer for Python (pip) in python and import iris package in python source code. 

import iris
class Solution():
    iris.connection()

thanks!

Hi

I get the following error when I am trying to create a linked server connection via MS OLE DB Provider for ODBC Drivers in MS SQL Server Management Studio. The message I get is:

The OLE DB provider "MSDASQL" for linked server "IRIS" reported an error. The provider did not give any information about the error.
Cannot initialize the data source object of OLE DB provider "MSDASQL" for linked server "IRIS". (Framework Microsoft SqlClient Data Provider)

I have setup the InterSystems ODBC setting on the server. Have enabled a number SPN settings but still getting this error

The full error message is :

Hi,

I'm very new to InterSystems  Health Connect so may be doing something silly...

I'm trying to link to an Oracle DB view using the Link Table Wizard in the Management Portal. The wizard finds the view, but when I select it and click the 'next' button I get an error on the 'Select Columns' screen: 'ERROR #5534: Columns error' (and no columns show in the wizard). I've tried on several views and tables in the same DB but keep hitting the same error.

I have previously successfully mapped a view and table from the same DB and am not sure what I am doing differently. Any suggestions appreciated!