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Comparing FME with Meltano and Weld

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

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Weld vs FME vs Meltano

WeldFMEMeltano
Connectors200+450+600+
Price$99 / 5M Active RowsPer-seat for FME Desktop ($2,000+/year) and per-core for FME Server (custom)free (self-hosted), custom (managed), paid support packages
Free tier
LocationEUSurrey, BC, Canada (Safe Software HQ)US
Extract data (ETL)
Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL)
Transformations
AI Assistant
On-Premise
Orchestration
Lineage
Version control
Load to/from ExcelYes (via Excel reader/writer)
Load to/from Google Sheets
Two-Way Sync
dbt Core Integration
dbt Cloud Integration
OpenAPI / Developer API
G2 rating4.84.74.9

Overview

FME in Short

FME (by Safe Software) is a data integration and transformation platform primarily focused on spatial and GIS data, but it also supports a wide range of non-spatial ETL. It provides a graphical workspace where users can build data pipelines, handling over 450 formats and applications, with strong data quality and validation capabilities.

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Pros

  • Supports 450+ data formats, making it ideal for GIS and non-GIS integration.

  • Graphical Workspaces with extensive transformer library for spatial (coordinate reprojection, topology) and non-spatial transformations (joins, data cleansing).

  • FME Server enables automated scheduling, breakout clustered processing, and REST API for triggering workflows.

  • Strong data validation and quality features—users can apply conditional checks and notifications when data doesn’t meet criteria.

Cons

  • High licensing costs for desktop (FME Desktop) and server components; often priced per core for server deployments.

  • Primarily geared toward GIS/spatial use cases; non-spatial ETL use is possible but the interface and transformers are optimized for spatial workflows.

  • Large learning curve for complex workspaces—dragging many transformers can become unwieldy visually.

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.

Overview

Meltano in Short

Meltano is an open-source data integration platform, similar to Airbyte, that enables businesses to build and manage their own data pipelines. It offers a wide range of connectors for databases, APIs, application logs, and other data sources. Meltano also supports robust data transformation and orchestration capabilities, making it easier to customize and automate workflows. It integrates seamlessly with popular cloud data warehouses, making it a flexible choice for modern data teams looking to manage their end-to-end data stack.

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Pros

  • Open-source platform

  • A really large number of connectors through Singer

  • Offer an SDK to more easily build Singer taps and targets

  • Flexibility in Deployment

Cons

  • No fully managed options so you need to deploy yourself (in Beta though)

  • Requires high maintenance

  • Limited data transformation capabilities (only through deep integration with DBT)

  • Only has a limited number of connectors that are natively built outside of Singer

Reviews & Quotes

As a user on G2 puts it::

What I like about Meltano

All the managerial tasks are handled under the hood, leaving you to focus on getting or consuming the data you need.

What I dislike about Meltano

With so many features baked into Meltano, navigating the documentation can be challenging. However, I've gotten around this by using Bing AI search, which brings me the answer immediately.

Overview

Weld in Short

Weld is a powerful ETL platform that seamlessly integrates ELT, data transformations, reverse ETL, and AI-assisted features into one user-friendly solution. With its intuitive interface, Weld makes it easy for anyone, regardless of technical expertise, to build and manage data workflows. Known for its premium quality connectors, all built in-house, Weld ensures the highest quality and reliability for its users. It is designed to handle large datasets with near real-time data synchronization, making it ideal for modern data teams that require robust and efficient data integration solutions. Weld also leverages AI to automate repetitive tasks, optimize workflows, and enhance data transformation capabilities, ensuring maximum efficiency and productivity. Users can combine data from a wide variety of sources, including marketing platforms, CRMs, e-commerce platforms like Shopify, APIs, databases, Excel, Google Sheets, and more, providing a single source of truth for all their data.

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Pros

  • Lineage, orchestration, and workflow features

  • Ability to handle large datasets and near real-time data sync

  • ETL + reverse ETL in one

  • User-friendly and easy to set up

  • Flat monthly pricing model

  • 200+ connectors (Shopify, HubSpot, etc.)

  • AI assistant

Cons

  • Requires some technical knowledge around data warehousing and SQL

  • Limited features for advanced data teams

  • Focused on cloud data warehouses

Reviews & Quotes

A reviewer on G2 said:

What I like about Weld

First and foremost, Weld is incredibly user-friendly. The graphical interface is intuitive, which makes it easy to build data workflows quickly and efficiently. Even with little experience in SQL and pipeline management, we found that Weld was straightforward and easy to use. What really impressed me, however, was Weld's flexibility. It was able to handle data from a wide variety of sources, including SQL databases, Google Sheets, and even APIs. The solution also allowed us to customize my data transformations in a way that best suited my needs. Whether I needed to clean data, join tables, or aggregate data, Weld had the necessary tools to accomplish the task. Weld's performance was also exceptional. I was able to run large-scale ETL jobs quickly and efficiently, with minimal downtime via a Snowflake instance and visualization via own-hosted Metabase. The solution's scalability meant that I could process more data without any issues. Another standout feature of Weld was its support. I never felt lost or unsure about how to use a particular feature, as the support team was always quick to respond to any questions or concerns that I had. Overall, I highly recommend Weld as an ETL solution. Its user-friendliness, flexibility, performance, and support make it an excellent choice for anyone looking to streamline their data integration processes. I will definitely be using Weld for all my ETL needs going forward.

What I dislike about Weld

Weld is still limited to a certain number of integrations - although the team is super interested to hear if you need custom integrations.

Feature-by-Feature Comparison

Feature
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FME

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Meltano

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Weld

Ease of Use & Interface

Side-by-side

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FME

FME’s Workbench is a desktop application where users connect Reader and Writer transformers to map and transform data. While powerful for spatial, the GUI can feel cluttered for workflows with hundreds of transformers.

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Meltano

Meltano is simple and easy to use for those with technical expertise, particularly due to its portability and command-line usability, but may be challenging for less technical users.

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Weld

Weld is highly praised for its user-friendly interface and intuitive design, which allows even users with minimal SQL experience to manage data workflows efficiently. This makes it an excellent choice for smaller data teams or businesses without extensive technical resources.

Pricing & Affordability

Side-by-side

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FME

FME Desktop licenses start around $2,000/year. FME Server pricing is per-core (often $20k+/core for an annual license). Expensive for small teams, but justified where spatial data integration is critical.

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Meltano

Meltano is open-source and free to use, making it highly affordable, but requires significant investment in deployment and maintenance, especially without a fully managed option.

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Weld

Weld offers a straightforward and competitive pricing model, starting at $79 for 5 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises.

Feature Set

Side-by-side

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FME

Supports reading/writing 450+ formats (GIS, CAD, JSON, XML, databases), transformer library (spatial & non-spatial), workflow orchestration via FME Server, automation (event-based, scheduled), and REST API endpoints for triggering.

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Meltano

The platform offers extensive integration options, including support for data transformation and orchestration, but relies heavily on the Singer framework, which can limit capabilities.

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Weld

Weld integrates ELT, data transformations, and reverse ETL all within one platform. It also provides advanced features such as data lineage, orchestration, workflow management, and an AI assistant, which helps in automating repetitive tasks and optimizing workflows.

Flexibility & Customization

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FME

Users can embed Python, R, or Shell scripts within transformers for custom logic. FME Server can be deployed in any environment (on-prem, AWS, Azure) and scaled horizontally. However, no built-in data catalog or lineage; separate tools needed.

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Meltano

Meltano is highly flexible for advanced users who can manage their own deployments and build on the platform, but it requires substantial maintenance and lacks a fully managed option.

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Weld

Weld offers advanced SQL modeling and transformations directly within its platform with the help of AI, providing users with unparalleled control and flexibility over their data. Leveraging its powerful AI capabilities, Weld automates repetitive tasks and optimizes data workflows, allowing teams to focus on getting value and insights. Additionally, Weld's custom connector framework enables users to build connectors to any API, making it easy to integrate new data sources and tailor data pipelines to meet specific business needs. This flexibility is particularly beneficial for teams looking to customize their data integration processes extensively and maximize the utility of their data without needing external tools.

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