What I like about Dell Boomi
“Boomi’s AtomSphere makes deploying integration processes easy—Atommachines can run anywhere (cloud or on-prem), and the visual interface is intuitive for building mappings.”
You’re comparing Dell Boomi vs FME vs Weld. Explore how they differ on connectors, pricing, and features.


Loved by data teams from around the world
| Weld | Dell Boomi | FME | |
|---|---|---|---|
| Connectors | 200+ | 200+ | 450+ |
| Price | $99 / 5M Active Rows | Subscription-based (per Atom/connection; starts ~$1000/month) | Per-seat for FME Desktop ($2,000+/year) and per-core for FME Server (custom) |
| Free tier | |||
| Location | EU | Austin, TX, USA | Surrey, BC, Canada (Safe Software HQ) |
| Extract data (ETL) | |||
| Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL) | |||
| Transformations | |||
| AI Assistant | |||
| On-Premise | |||
| Orchestration | |||
| Lineage | |||
| Version control | |||
| Load to/from Excel | Yes (via ODBC/JDBC) | Yes (via Excel reader/writer) | |
| Load to/from Google Sheets | |||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4.3 | 4.7 |
Overview
Dell Boomi AtomSphere is a cloud-native iPaaS that provides ETL, API management, B2B/EDI integration, and workflow automation via a visual “Atom” runtime architecture. It supports 200+ connectors (SaaS, on-prem, databases) and allows users to build, deploy, and manage integration processes (called Atoms) in a drag-and-drop interface. Boomi’s AtomSphere runs on a lightweight runtime engine that can be deployed in the cloud or on-premise for hybrid scenarios.

200+ connectors for SaaS, on-prem, and big data sources.
Cloud-native or on-prem Atom runtime allows hybrid deployments.
Visual process designer with drag-and-drop mapping, enriched by shape-specific logic (e.g., function, decision, loop).
Built-in error handling, version control, and CI/CD integration.
Costly licensing structure (per-connection, per-Atom), which can escalate for high throughput or many connectors.
Complex transformations sometimes still require scripting (JavaScript/Groovy), reducing low-code benefits for advanced scenarios.
Learning curve: mastering Atoms, Molecules, and hybrid architecture requires time, particularly for non-technical users.
Dell Boomi Documentation:
“Boomi’s AtomSphere makes deploying integration processes easy—Atommachines can run anywhere (cloud or on-prem), and the visual interface is intuitive for building mappings.”
“Licensing can be expensive, especially for high-volume data. Complex integrations can require coding despite the low-code promise.”
Overview
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.

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.
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.
FME Product Overview:
“FME’s ability to handle complex spatial transformations and 450+ formats is unmatched. The drag-and-drop workspace builder drastically speeds up geospatial ETL.”
“Licensing can be expensive for smaller organizations. Focus on spatial means some general ETL features are less polished than GIS-specific functions.”
Overview
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.
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
Requires some technical knowledge around data warehousing and SQL
Limited features for advanced data teams
Focused on cloud data warehouses
A reviewer on G2 said:
“Weld is still limited to a certain number of integrations - although the team is super interested to hear if you need custom integrations.”




Side-by-side

Boomi’s Integration Builder uses a web-based canvas to create process flows. Connectors and maps are configured via dialogs. Error-handling, version control, and deployment controls are integrated. Some users find building very complex workflows cumbersome despite the visual design.

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.
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.
Side-by-side
Boomi’s Integration Builder uses a web-based canvas to create process flows. Connectors and maps are configured via dialogs. Error-handling, version control, and deployment controls are integrated. Some users find building very complex workflows cumbersome despite the visual design.
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.
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.
Side-by-side

Boomi’s pricing is multi-faceted—permanent Atom licenses, per-connection pricing, and usage-based charges for transactions. SMBs may need to request custom quotes to stay within budget.

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.
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.
Side-by-side
Boomi’s pricing is multi-faceted—permanent Atom licenses, per-connection pricing, and usage-based charges for transactions. SMBs may need to request custom quotes to stay within budget.
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.
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.
Side-by-side

Features: ETL/ELT processes, API management, EDI/B2B integration, workflow automation, data quality, and master data management. It also offers training, community forums, and professional services.

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.
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.
Side-by-side
Features: ETL/ELT processes, API management, EDI/B2B integration, workflow automation, data quality, and master data management. It also offers training, community forums, and professional services.
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.
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.
Side-by-side

Custom scripting is supported via Groovy or JavaScript for complex transforms. Atoms can be deployed virtually anywhere for hybrid use cases. However, you rely on Boomi for core engine updates; it’s not open-source.

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.
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.
Side-by-side
Custom scripting is supported via Groovy or JavaScript for complex transforms. Atoms can be deployed virtually anywhere for hybrid use cases. However, you rely on Boomi for core engine updates; it’s not open-source.
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.
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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