Niko Nelissen
Data platforms and iPaaS tools are widely used to implement ETL pipelines in all kinds of flavours. These pipelines take data from various sources – for example business applications – and centralise the data in a data warehouse. Once the data is in a data warehouse, the next step is often a “reverse” ETL flow where data is synced back into business applications.
Furthermore, the data warehouse can be used to set up alerting rules for business teams, it can be used to produce custom reports and a data warehouse can even feed data into an in-house AI chatbot (using an LLM).
It’s fair to say that there are many different use cases for data integration and for data activation and it’s clear that both data platforms and iPaaS tools play a crucial role in all of these data use cases.
The challenge with many of the data platforms and iPaaS tools on the market is that they are either too complex to use, or that they are too simplistic and limited in functionality, in order to implement specific data solutions:
We can distinguish two major activity types in both data integration and data activation:
What has been lacking on the market is a data platform or iPaaS that seamlessly integrates SQL and Python into a single unified workbench. That’s why our team has built Peliqan.io, a unique approach to data integration and data activation that allows users to seamlessly combine SQL and low-code Python.
In this article we’ll dive into the concept of low-code Python, what it means and how it’s different from “classic” coding in Python.
Low-code basically means that you need less lines of code compared to “classic” coding, which makes the code easier to write, easier to understand and easier to maintain.
Low-code Python allows users to use one of the most popular scripting languages in the world – Python – with all the benefits of the low-code paradigm. Low-code Python saves time and allows users with a less technical background to implement the solutions that they need.
Many iPaaS platforms use a no-code approach for their main UI, which usually looks like workflows with blocks that users click together in a drag & drop interface. This approach is great for various automation flows that perform “if this then that” logic. However, for data-centric use cases, the no-code approach tends to create very complex workflows with hundreds of blocks, which defeats the purpose of having a visual representation.
That’s why a low-code approach combines the best of both worlds: users do not have to be full-fledged developers and can implement data integration solutions with small scripts, without being hindered by the inherent limitations of a visual workflow editor.
Peliqan’s low-code Python for data integration and data activation consists of 3 main pillars:
We’ll discuss each of these pillars in the next paragraphs.
The framework provides patterns or “blueprints” on how to implement various data integration use cases. For example if you want to set up a data sync from a source to a destination, you have to think about various aspects such as processing the source data incrementally and doing “upserts” in the target to avoid duplicates. The Peliqan.io framework provides blueprints for such a data synchronisation so that the correct pattern is implemented from the start.
The blueprints are implemented using a set of components and the components provide rich functions so that common actions can be performed with only one line of code.
A great example is the “upsert” when writing data to a target, for example a CRM system. An upsert means that you either add a new record if it does not exist or update the existing record if it does. The upsert requires a lookup first and then performs the insert or update. Peliqan allows you to perform an upsert to over 100 target systems (DB’s, ERP, CRM, accounting etc.) with just one line of code. This makes your code concise, easy to understand and you don’t have to reinvent the wheel.
Here are a few example of components that Peliqan.io provides out-of-the-box as part of its low-code Python solution:
The Peliqan module provides a wide range of functions to work with data:
Streamlit is a wonderful module for data-centric user interaction. Streamlit is built-in into Peliqan and allows you to build data apps with just a few lines of code. Streamlit comes with a wide range of UI components, for example input fields, dropdows, data visualization (charts), components for a Chatbot and much more.
One of the most unique features of Peliqan’s low-code Python environment is the API wrappers for 100+ business SaaS applications. These API wrappers allow you to interact with SaaS APIs with a single line of code. The wrapper will handle all the specifics of the API:
Here’s an example to add a Company in Hubspot (CRM):
result = hubspot.add("company", {"name": "ACME", "country": "UK"})
Peliqan.io provides a unified workbench to write, test, deploy and maintain low-code Python scripts and SQL queries for data integration and data activation, all in one beautiful web-based environment. SQL and Python can be seamlessly combined.
Peliqan provides a web-based IDE to write scripts, run them and expose scripts as API endpoints. Scripts can be scheduled to run e.g. every minute, hour or every day. Logs are automatically stored for every run. Peliqan can receive and queue incoming webhooks from any source, without the need for any additional configuration.
Next to the core Python and SQL IDE, Peliqan also provides a Marketplace that allows for single click deployment of common building blocks that are needed in a data-centric project. The Marketplace is essentially a provisioning layer for infrastructure, so that users do not lose time figuring out how to install, configure and host tools that they need such a an SFTP server, a vector database, a BI tool such as Metabase or Superset, a Jupyter notebook or a search engine such as ElasticSearch.
In order to help users write correct scripts, Peliqan provides various built-in aids to support you:
Low-code Python is a new paradigm, introduced by Peliqan.io, to empower users that want to implement data integration and data activation solutions efficiently without the need to become a full-fledged data engineer. Low-code Python, combined with SQL, is the cornerstone of the Peliqan.io all-in-one data platform and provides a modern alternative to data platforms that are too complex to use on the one hand, and iPaaS platforms that are not data-centric on the other.
Low-code Python is a programming paradigm that reduces the amount of code needed to build and maintain data integration and activation solutions. It allows users to leverage Python, one of the most popular scripting languages, with a low-code approach, making it accessible for those with less technical expertise while still maintaining flexibility and power.
Low-code coding refers to a development approach where minimal coding is required. It typically involves using predefined components, templates, and frameworks to build applications or automate tasks with fewer lines of code, making the development process faster, easier, and more maintainable.
Low-code and no-code platforms are becoming increasingly popular as they democratize software development, allowing non-developers to create applications and automate workflows. While they won’t replace traditional coding entirely, they will continue to grow in importance, especially for businesses that need to move quickly and adapt to changing requirements.
Niko Nelissen is the founder of Peliqan. Before Peliqan, Niko founded Blendr.io, a no-code iPaaS integration platform. Blendr.io was acquired by Qlik in 2020 and Niko became Senior Director of Product Management for Automation at Qlik. Niko’s primary interest is in the modern data stack, ML/AI as well as SaaS software in general and building disruptive technology.
Customer Data Platforms (CDPs): What it is & top tools Table of Contents Customer Data Platforms (CDPs) CDPs have emerged as essential tools for businesses aiming to unify customer information and power personalized marketing. A
Top Matillion Alternatives & Competitors Table of Contents Top Matillion Alternatives & Competitors in 2025 Matillion is a popular cloud-native ETL/ELT platform used to load and transform data in modern data warehouses (e.g. Snowflake, Redshift, BigQuery)
Top CData Alternatives & Competitors Table of Contents Top CData Alternatives & Competitors in 2025 CData has established itself as a leader in data connectivity with 300+ connectors and recognition in the 2024 Gartner Magic Quadrant.
CIC Hospitality saves 40+ hours per month by fully automating board reports. Their data is combined and unified from 50+ sources.
Heylog integrates TMS systems with real-time 2-way data sync. Heylog activates transport data using APIs, events and MQTT.
Globis SaaS ERP activates customer data to predict container arrivals using machine learning.
