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.”
You’re comparing FME vs Informatica PowerCenter vs Weld. Explore how they differ on connectors, pricing, and features.


Loved by data teams from around the world
| Weld | FME | Informatica PowerCenter | |
|---|---|---|---|
| Connectors | 200+ | 450+ | 200+ |
| Price | $99 / 5M Active Rows | Per-seat for FME Desktop ($2,000+/year) and per-core for FME Server (custom) | Enterprise licensing (six-figure annual contracts) |
| Free tier | |||
| Location | EU | Surrey, BC, Canada (Safe Software HQ) | Redwood City, CA, USA (Informatica 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 Excel reader/writer) | Yes (flat-file integration) | |
| Load to/from Google Sheets | |||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4.7 | 4.3 |
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
Informatica PowerCenter is a legacy enterprise-grade ETL platform that provides a visual designer, metadata management, scheduling, and monitoring for complex, large-scale ETL workloads. It supports a vast range of sources (mainframes, relational, NoSQL, cloud) and advanced transformations (data quality, profiling, master data management) within the Informatica ecosystem.

Extremely powerful and scalable for enterprise ETL with parallel processing and pushdown optimization.
Comprehensive transformation library, data quality, and metadata management integrated in the platform.
Robust scheduling and workflow orchestration with detailed logging and recovery capabilities.
Supports heterogeneous environments: on-prem, cloud, hybrid, and mainframe data sources.
High total cost of ownership: expensive licensing, dedicated infrastructure, and specialized admins.
User interface is dated; development and maintenance require specialized training, increasing time to onboard new users.
Less agility for rapidly changing data needs vs. modern cloud-native ETL tools; upgrades and patches are time-consuming processes.
G2 Reviews:
“Informatica powercenter has been a classic , it has been in the industry for around 30 years and still is very relavant to the point , provide every possible connector and provides best mapping tools.”
“the UI looks very old and sometimes it is very difficult to handle big big mappings as it needs lot of experience”
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

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.

PowerCenter’s Designer and Workflow Manager GUIs are comprehensive but dated. Developers need formal training to use transformation and mapping components effectively. The metadata integration assists with governance but adds complexity.
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
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.
PowerCenter’s Designer and Workflow Manager GUIs are comprehensive but dated. Developers need formal training to use transformation and mapping components effectively. The metadata integration assists with governance but adds complexity.
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

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.

Pricing is custom enterprise quotes—often $100k+ per year depending on nodes and users. Best for large enterprises that need high SLAs and rich feature sets; impractical for startups or small teams.
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
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.
Pricing is custom enterprise quotes—often $100k+ per year depending on nodes and users. Best for large enterprises that need high SLAs and rich feature sets; impractical for startups or small teams.
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

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.

Includes: visual mapping designer, advanced transformations (data cleansing, lookups, aggregation), parallel processing, workflow orchestration, metadata manager, data quality, master data management, and extensive connectivity (mainframe to cloud).
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
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.
Includes: visual mapping designer, advanced transformations (data cleansing, lookups, aggregation), parallel processing, workflow orchestration, metadata manager, data quality, master data management, and extensive connectivity (mainframe to cloud).
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

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.

Highly customizable via Expression Transformations, Java Transformations, and stored procedure calls. Integration with command tasks allows custom scripts. However, it’s not open-source; you rely on Informatica for feature updates.
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
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.
Highly customizable via Expression Transformations, Java Transformations, and stored procedure calls. Integration with command tasks allows custom scripts. However, it’s not open-source; you rely on Informatica for feature updates.
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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