Prisma ORM: Unable to Retrieve Data Within a Specific Longitude and Latitude Range

What will you learn?

In this comprehensive guide, you will delve into resolving the challenge of querying data within a specific range of longitude and latitude using Prisma ORM. Learn how to leverage raw SQL queries and geospatial functions for precise data retrieval.

Introduction to the Problem and Solution

Working with geospatial data in databases through an ORM like Prisma necessitates the ability to fetch data based on specific geographic coordinates. The issue arises when querying data within longitude and latitude ranges. To address this, we can employ raw database queries in Prisma alongside the geospatial functionalities provided by the underlying database system.

By integrating raw SQL queries into our Prisma workflow, we gain direct access to the database’s geospatial capabilities for accurate data selection based on longitude and latitude ranges.


Here is an example of executing a query using raw SQL in Prisma to retrieve data within a designated longitude and latitude range:

# Importing necessary modules from Prisma
from prisma import Client

# Initialize the Prisma client
prisma = Client()

# Define latitude and longitude range values
min_lat = 40.0
max_lat = 42.0

min_lon = -75.0 
max_lon = -73.0

# Execute raw SQL query to fetch records within the specified range
result = primsa.execute_raw(
    "SELECT * FROM your_table_name WHERE lat BETWEEN %s AND %s AND lon BETWEEN %s AND %s",

# Copyright PHD

Note: Replace your_table_name with your actual table name containing geo-coordinates.


The provided code snippet showcases how raw SQL queries can be utilized in conjunction with Prisma functionality to extract records falling within a defined geographical boundary. Here’s a breakdown: – Import essential modules from Prisma. – Establish a connection with our Prima client. – Set minimum and maximum values for latitude (lat) and longitude (lon). – Utilize execute_raw() method from Prima client object to run custom SQL query directly against our database table. – The executed query selects records where both latitude (lat) falls between min_lat & max_lat, as well as where longitude (lon) falls between min_lon & max_lon.

This approach empowers precise control over querying geospatial data effectively via direct access through raw SQL commands while benefiting from other features offered by Prima ORM.

    How can I efficiently handle geospatial queries using an ORM like Prima?

    Efficiently manage geospatial queries by combining raw SQL queries with geospatial functions supported by your database system for optimal performance.

    Can I integrate external APIs for mapping services into my application that utilizes spatial data?

    Yes, seamlessly integrate various mapping APIs such as Google Maps or Mapbox API with your spatially-aware application logic.

    Is there any advantage in storing geographical coordinates as separate columns rather than combined?

    Storing latitude and longitude as distinct columns provides better flexibility during querying operations involving spatial calculations compared to merged coordinate storage formats.

    And more…


    In conclusion, effectively handling queries involving geographical coordinates within specific ranges requires a strategic blend of high-level ORMs like Prismas, alongside low-level interactions via custom raw SQL statements for targeted data retrieval tasks. By adeptly merging these approaches, developers gain meticulous control over their geospatial databases while upholding code elegance through efficient ORM utilization.

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