I still see the difference, maybe it is the version of IRIS and drivers.

Following are the version of various software I am using (and IRIS and Python code is running on same host).

IRIS version: IRIS for Windows (x86-64) 2024.3 (Build 206U) Fri Oct 11 2024 17:13:28 EDT

Python: Python 3.11.9

SQLAlchemy: Version: 2.0.0

sqlalchemy-iris: 0.17.0

intersystems_irispython: 5.1.0

Thanks for this post, I noticed that doing insert from SQLAlchemy is slower than when is done directly from Python. So I wrote following code, in one case I can getting connection string from SQLAlchemy and in second case getting it from Python. Exact code is 50% slower when connection is obtained from SQLAlchemy. Any thoughts?

The code is below, only difference between the two run is how I am setting the connection variable.

import pandas as pd

from sqlalchemy import create_engine

import numpy as np

import time

import iris

# Create the SQLAlchemy engine

DATABASE_URL = "iris+intersystems://XXX:XXX@localhost:1972/USER"

engine = create_engine(DATABASE_URL, echo=True)

args = {'hostname':'localhost', 'port':1972, 'namespace':'USER', 'username':'XXX', 'password':'XXX'}

# connection = iris.connect(**args)

connection = engine.raw_connection()

# Generate data for each row (49 fields)

num_records = 100000

# Define SQL insert statement

sql_insert = "INSERT INTO SQLUser . test_table ( field_0 , field_1 , field_2 , field_3 , field_4 , field_5 , field_6 , field_7 , field_8 , field_9 , field_10 , field_11 , field_12 , field_13 , field_14 , field_15 , field_16 , field_17 , field_18 , field_19 , field_20 , field_21 , field_22 , field_23 , field_24 , field_25 , field_26 , field_27 , field_28 , field_29 , field_30 , field_31 , field_32 , field_33 , field_34 , field_35 , field_36 , field_37 , field_38 , field_39 , field_40 , field_41 , field_42 , field_43 , field_44 , field_45 , field_46 , field_47 , field_48 ) VALUES ( ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? , ? ) "

record_values = []

# Execute SQL insert

try:

    start_time = time.perf_counter()  # Capture start time

    batch = 0

    cursor = connection.cursor()

    for _ in range(num_records):

        record_values = [np.random.rand() for _ in range(49)]

        cursor.execute(sql_insert, record_values)

        batch = batch + 1

        if batch >= 10000:

            connection.commit()

            batch = 0

    # print("Record inserted successfully!")

    connection.commit()

    end_time = time.perf_counter()  # Capture end time

    elapsed_time = end_time - start_time

    print(f"Time taken: {elapsed_time} seconds to insert {num_records} at ", num_records/elapsed_time, " records per second.")

except Exception as e:

    print("Error inserting record:", e)

finally:

    cursor.close()

    connection.close()

    engine.dispose()