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Weld vs Equals vs FME

You’re comparing Weld vs Equals vs FME. Explore how they differ on connectors, pricing, and features. Ed Logo

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Weld vs Equals vs FME

FeatureWeldEqualsFME
Core Platform
Price
$79 / 5M Active Rows
Custom (not publicly disclosed)
FME Desktop ~$2,000+/year per seat; FME Server per-core (custom pricing)
Free tier
No
No
No
Location
DK, (EU)
US
Surrey, BC, Canada
Connectors & Sync
Connectors
200+
450+
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
Yes
AI Assistant
Yes
No
No
dbt Core Integration
Yes
No
No
dbt Cloud Integration
Yes
No
No
Governance & DevOps
Orchestration
Yes
No
Yes
Lineage
Yes
No
No
Version control
Yes
No
No
On-Premise
No
No
Yes
OpenAPI / Developer API
Yes
No
Yes
Integrations
Load to/from Excel
Yes
No
Yes (Excel reader/writer)
Load to/from Google Sheets
Yes
No
No
Ratings
G2 rating
4.8
4.7

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.

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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

Equals in Short

Equals is an all-in-one GTM analytics platform that combines data ingestion, transformation, and analysis in a unified interface. It automatically syncs data from sources such as Salesforce, HubSpot, Stripe, and SQL databases into an embedded Snowflake warehouse, and presents analysis through a spreadsheet-style BI layer tailored for revenue and pipeline metrics.

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Pros

  • Integrated ELT with automated syncs for Salesforce, HubSpot, Stripe, SQL sources, and more.

  • Includes a managed Snowflake warehouse—no infrastructure setup or maintenance required.

  • Spreadsheet-based BI interface with live queries for analysis and reporting.

  • Pre-built GTM templates for pipeline, ARR, churn, and revenue metrics.

  • Slack/email alerting for scheduled or triggered notifications.

Cons

  • Primarily optimized for GTM and revenue analytics rather than broad ETL use cases.

  • Custom SQL is required for more advanced modeling or non-template scenarios.

  • Costs can increase if Snowflake consumption grows beyond base package levels.

Reviews & Quotes

From an Equals customer success story:

What I like about Equals

Within a week, we had a pipeline performance dashboard up and running. Building something similar ourselves would have taken 3+ months.

What I dislike about Equals

Some advanced customization options beyond the built-in GTM templates require SQL knowledge and comfort with the underlying warehouse.

Overview

FME in Short

FME (by Safe Software) is a data integration and transformation platform with a strong focus on spatial and GIS data. It also supports a wide range of non-spatial ETL through a graphical workspace. With support for over 450 formats and applications, FME is well-suited for organizations needing advanced spatial transformations, validation, and complex data workflows.

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Pros

  • Supports 450+ data formats, including extensive GIS, CAD, database, and file types.

  • Graphical Workbench with a large transformer library for spatial and non-spatial transformations.

  • FME Server adds automation, scheduling, job orchestration, REST APIs, and distributed processing.

  • Built-in data validation and quality tools, enabling conditional checks and notifications.

Cons

  • Licensing costs for FME Desktop and FME Server can be high, especially for small organizations.

  • Primarily optimized for spatial workflows; non-spatial ETL is supported but not the main focus.

  • Complex workspaces can become visually cluttered and require experience to manage efficiently.

Reviews & Quotes

FME Product Overview:

What I like about FME

FME’s ability to handle complex spatial transformations and 450+ formats is unmatched. The drag-and-drop workspace builder drastically speeds up geospatial ETL.

What I dislike about FME

Licensing can be expensive for smaller organizations. Focus on spatial means some general ETL features are less polished than GIS-specific functions.

Feature-by-Feature Comparison

Feature
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Ease of Use & Interface

Side-by-side

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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.

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Equals uses a spreadsheet interface familiar to analysts and operations teams, combined with direct SQL access for more technical users. GTM-focused templates accelerate dashboard creation and reduce configuration time.

fme logo

FME Workbench offers a desktop UI for visually designing data flows using Readers, Writers, and Transformers. It is powerful for spatial data but can become cluttered when handling large, complex pipelines.

Pricing & Affordability

Side-by-side

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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.

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Equals uses a custom-quote pricing model that includes ELT, transformations, and a managed Snowflake warehouse. Costs scale with data usage and compute consumption inside Snowflake, which may increase as data volume grows.

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FME Desktop licensing typically starts around $2,000 per year. FME Server is licensed per core and can exceed $20k per core annually, making it more suitable for mid-sized and enterprise GIS teams.

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.

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Key features include automated ELT from GTM systems, a built-in Snowflake warehouse, spreadsheet-based BI, pre-defined revenue dashboards, scheduling, and alerting. Designed specifically for GTM analytics workflows.

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Supports 450+ formats, spatial and non-spatial transformations, workflow orchestration via FME Server, event- or schedule-based automation, REST APIs, and strong validation capabilities.

Flexibility & Customization

Side-by-side

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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.

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Users can extend beyond templates using SQL for custom transformations and modeling. Advanced customization depends on SQL proficiency, but the spreadsheet layer covers most operational analytics needs.

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Users can embed Python, R, or Shell scripts for advanced logic. FME Server supports deployment on-prem or in cloud environments and scales horizontally. Data lineage and cataloging are not built in and require separate systems.

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CUSTOMER STORIES

The latest success stories from data-driven companies

Jacob Poulsen, Head of Marketing Expansion at Flatpay logo

How Flatpay optimized marketing efficiency with Weld

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
Rodrigo Andres Valle, Data Engineer at Holafly logo

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.
Rodrigo Andres Valle, Data Engineer at Holafly
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.
Temur Makhsudov, Head of BI and Operations
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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