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Weld vs Matillion vs Polar Analytics

You’re comparing Weld vs Matillion vs Polar Analytics. Explore how they differ on connectors, pricing, and features. Ed Logo

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VS
matillion logo
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Weld vs Matillion vs Polar Analytics

FeatureWeldMatillionPolar Analytics
Core Platform
Price
$79 / 5M Active Rows
Consumption-based, credits
$800 / month
Free tier
No
No
No
Location
DK, (EU)
UK
FR
Connectors & Sync
Connectors
200+
150+
45+
Extract data (ETL)
Yes
Yes
Yes
Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL)
Yes
No
No
Two-Way Sync
Yes
No
No
Transformations & AI
Transformations
Yes
Yes
No
AI Assistant
Yes
Yes
No
dbt Core Integration
Yes
No
No
dbt Cloud Integration
Yes
No
No
Governance & DevOps
Orchestration
Yes
Yes
No
Lineage
Yes
Yes
No
Version control
Yes
Yes
No
On-Premise
No
No
No
OpenAPI / Developer API
Yes
Yes
No
Integrations
Load to/from Excel
Yes
Yes
No
Load to/from Google Sheets
Yes
Yes
No
Ratings
G2 rating
4.8
4.3
4.5

Overview

Weld in Short

Weld is a unified ELT and data activation platform that combines ingestion, modeling, transformations, orchestration, lineage, and reverse ETL in a single SaaS interface. With premium in-house–built connectors, an intuitive UI, and near real-time syncs, Weld enables both technical and non-technical users to create and manage data workflows efficiently. Weld also includes an AI assistant to support SQL modeling, generate transformations, and streamline repetitive tasks. Teams can ingest data from a wide range of sources—including marketing platforms, CRMs, databases, Google Sheets, Excel, and APIs—into their cloud data warehouse and activate it back into business tools.

weld logo

Pros

  • Lineage, orchestration, and workflow features included by default

  • Handles large datasets and near real-time data sync

  • ELT and reverse ETL in one platform

  • User-friendly interface with minimal setup required

  • Flat, predictable monthly pricing model

  • 200+ in-house–built, high-quality connectors

  • AI assistant for modeling and transformations

Cons

  • Some SQL knowledge is useful for advanced modeling

  • Optimized for cloud-warehouse workflows (Snowflake, BigQuery, Redshift, etc.)

  • Feature set is streamlined for modern ELT/activation use cases

Reviews & Quotes

A reviewer on G2 said:

What I like about Weld

Weld’s graphical interface is intuitive and easy to work with, even for teams with limited SQL experience. Its flexibility across sources—from databases to Google Sheets and APIs—made onboarding smooth, and performance across larger workloads was consistently strong. Support was responsive and helpful throughout our setup and ongoing use.

Overview

Matillion in Short

Matillion is a cloud-native data integration and transformation platform built for modern cloud data warehouses such as Snowflake, Redshift, Databricks, and BigQuery. It provides visual, low-code pipeline development with strong orchestration and transformation capabilities, making it suitable for enterprise-scale workloads. While powerful, it is often considered more complex and better suited for mature data teams.

matillion logo

Pros

  • Large library of connectors

  • Strong orchestration and transformation features

  • Suitable for large enterprises with complex data workloads

  • Supports both ETL and ELT patterns

  • Flexible, visual pipeline development

Cons

  • Can be expensive for smaller teams

  • Steep learning curve for non-technical users

  • Overkill for simpler or smaller data operations

Reviews & Quotes

A reviewer on G2 said::

What I like about Matillion

Built-in connectors to many systems, ability to create custom connectors, and an active community with quick responses to technical questions.

What I dislike about Matillion

Some components feel clunky, and certain cloud features lag behind older versions.

Overview

Polar Analytics in Short

Polar Analytics is an all-in-one analytics platform tailored for ecommerce brands. It integrates marketing, sales, and operations data to help teams automate reporting and improve decision-making. Built on a dedicated Snowflake instance, it includes features like custom dashboards, attribution and AI-powered agents.

polar analytics logo

Pros

  • Tailored for DTC brands

  • Comprehensive marketing and sales insights

  • Easy integration with popular eCommerce platforms

  • User-friendly interface with powerful dashboards

  • Helps optimize marketing ROI with data-driven insights

Cons

  • Primarily focused on DTC, limiting broader use cases

  • Can be expensive for small brands

  • Advanced features may require some learning

Reviews & Quotes

From the Shopify App Store:

What I like about Polar Analytics

I have 4 shops and use Polar to give me an overview of all shops in one dashboard. Also, integration with Analytics and Klaviyo is perfect.

Feature-by-Feature Comparison

Feature
weld logo
matillion logo
polar analytics logo

Ease of Use & Interface

Side-by-side

weld logo

Weld’s interface is built for clarity and speed, enabling users with varying levels of technical experience to manage data pipelines and models efficiently. Its built-in lineage and orchestration tools provide transparency across workflows.

matillion logo

Matillion offers a visual interface but still requires technical knowledge to use effectively, especially for more advanced transformations and orchestration.

polar analytics logo

Polar emphasizes ease of use with a no-code setup and pre-built templates. Its Shopify-first approach resonates well with ecommerce users but may limit flexibility for technical teams.

Pricing & Affordability

Side-by-side

weld logo

Weld offers a simple and predictable pricing model starting at $79 for 5 million active rows. This flat, usage-transparent structure makes budgeting straightforward for small and medium-sized teams.

matillion logo

Matillion uses a consumption-based pricing model that can become costly as workloads grow, making it less accessible for smaller teams or early-stage companies.

polar analytics logo

Polar starts at a higher price point but includes a dedicated Snowflake instance, unlimited historical data, and support. It is designed for ecommerce brands prioritizing fast insights and ease of use over customizable data infrastructure.

Feature Set

Side-by-side

weld logo

Weld provides ELT ingestion, SQL-based transformations, reverse ETL activation, data lineage, orchestration, and workflow management in a single platform. Its AI assistant accelerates modeling and transformation tasks.

matillion logo

Matillion provides extensive transformation, orchestration, and data integration features with a large connector ecosystem. However, it focuses heavily on ETL/ELT and does not cover end-to-end data activation or reverse ETL.

polar analytics logo

The platform includes a data warehouse, semantic layer, first-party pixel, pre-built dashboards, and AI agents for marketers. It excels in ecommerce analytics but lacks advanced data orchestration or transformation features.

Flexibility & Customization

Side-by-side

weld logo

Users can model data using SQL enhanced by Weld’s AI assistant, automate workflows, and build custom connectors to any API. This provides strong flexibility for teams that want to tailor integrations and transformations within one platform.

matillion logo

Matillion is highly flexible for complex enterprise pipelines, but the platform’s depth can introduce complexity, making it less suitable for teams seeking a simple or lightweight solution.

polar analytics logo

Users can create custom reports and metrics, and define roles and permissions. However, deeper customization like SQL modeling or open APIs are limited compared to developer-centric tools.

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CUSTOMER STORIES

The latest success stories from data-driven companies

Jacob Poulsen, Head of Marketing Expansion at Flatpay logo

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One of the biggest impacts has been unlocking new ways to buy media. Before, we didn’t have the data to back up strategic decisions – now we do.
Jacob Poulsen, Head of Marketing Expansion at Flatpay
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How Holafly transformed data management and scaled globally with Weld

Before Weld, we had to rely on custom Python scripts and manual processes that were time-consuming and error-prone.
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Michael Howes, Head of Data & Insights at Dishoom logo

How Dishoom scaled data operations without scaling its team

We’re still a team of three, but we’re often doing far more than the equivalent of three full-time employees. That’s down to how we're able to leverage systems, data, and processes.
Michael Howes, Head of Data & Insights at Dishoom
Sven Hasenberg, CFO, VitaMoment logo

Inside VitaMoment’s Journey to KPI-Driven Growth and Data Ownership

We’ve always been a KPI-driven company. But we wanted to scale that mindset across every team member, every team, every decision.
Sven Hasenberg, CFO, VitaMoment
Temur Makhsudov, Head of BI and Operations logo

How Danish Endurance boosted profitability by 77 % and transformed data management with Weld

Before Weld, our data infrastructure was limited and we relied heavily on Excel files and custom Python scripts.
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Matias Voldby Drejer, BI Lead logo

How Female Invest centralized data management and saved resources with Weld

Weld has saved us a ton of time, from not having data ready to having a fully functional data warehouse and connectors.
Matias Voldby Drejer, BI Lead
Jonas Iversen, Tech Lead Data logo

How Soundboks streamlined data integration with Weld, S3, and Databricks

By integrating Weld, Amazon S3, and Databricks, Soundboks built a modern data pipeline that automates data ingestion, improves reporting, and provides up-to-date visibility into sales performance
Jonas Iversen, Tech Lead Data
Jens Karstoft, Chief Operating Officer at Roccamore logo

How Roccamore unlocked better business insights with Weld

We didn’t have a good data setup, so we lacked the business insights we needed. Weld has allowed us to set up a structured data infrastructure and access insights quickly.
Jens Karstoft, Chief Operating Officer at Roccamore

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