What I like about Informatica PowerCenter
“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.”
You’re comparing Informatica PowerCenter vs Pentaho Data Integration vs Weld. Explore how they differ on connectors, pricing, and features.


Loved by data teams from around the world
| Weld | Informatica PowerCenter | Pentaho Data Integration | |
|---|---|---|---|
| Connectors | 200+ | 200+ | 150+ |
| Price | $99 / 5M Active Rows | Enterprise licensing (six-figure annual contracts) | Community Edition: Free; Enterprise Edition: Custom pricing |
| Free tier | |||
| Location | EU | Redwood City, CA, USA (Informatica HQ) | Santa Clara, CA, USA (Hitachi Vantara 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 (flat-file integration) | Yes (Excel/CSV input/output) | |
| Load to/from Google Sheets | Yes (via Google Sheets plugin) | ||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4.3 | 4.1 |
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
Pentaho Data Integration (PDI), also known as Kettle, is an open-source ETL tool from Hitachi Vantara. It provides a graphical Spoon interface for building ETL transformations and jobs, supporting over 150 data sources (relational, NoSQL, cloud, files). PDI includes built-in steps for data cleansing, join, lookup, and can execute transformations in a clustered environment. It also integrates with Pentaho’s BI platform for analytics.

Open-source (Community Edition) with no licensing costs; Enterprise Edition provides additional features and support.
150+ connectors (databases, cloud storage, big data, files, NoSQL) and flexible step-based transformations.
Graphical Spoon interface for visual ETL job design; transformations can be previewed and tested in real-time.
Support for clustered execution (Carte server) for parallel processing and higher throughput.
Community Edition lacks advanced features (lineage, data quality, enterprise monitoring), requiring Enterprise Edition for production readiness.
Performance can suffer with very large data volumes if not properly tuned (Java memory, clustering).
User interface and user experience are dated compared to newer cloud-native ETL tools.
Pentaho Data Integration Overview:
“PDI’s free community edition and Spoon GUI allow rapid ETL prototyping; its step library is extensive, and clustering support is solid for scale.”
“Limited data quality features and slower development speed compared to modern cloud ETL. Community support can be slow for fixes.”
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

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.

Pentaho’s Spoon GUI uses a canvas paradigm: drag "steps" onto a transformation, connect them, and configure. While powerful, it can feel clunky, especially for very complex flows with many steps.
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
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.
Pentaho’s Spoon GUI uses a canvas paradigm: drag "steps" onto a transformation, connect them, and configure. While powerful, it can feel clunky, especially for very complex flows with many steps.
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

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.

The free Community Edition is attractive for experimentation. Enterprise Edition pricing is usage-based and includes support, lineag, and more; typically suited for mid-sized to large organizations.
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
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.
The free Community Edition is attractive for experimentation. Enterprise Edition pricing is usage-based and includes support, lineag, and more; typically suited for mid-sized to large organizations.
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

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).

PDI features: GUI-based transformation designer, job orchestration, data cleansing, lookups, joins, scripting (JavaScript, PDI’s built-in “User Defined Java Expression”), logging, clustering, and integration with Pentaho BI for reporting. Lineage and monitoring in Enterprise.
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
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).
PDI features: GUI-based transformation designer, job orchestration, data cleansing, lookups, joins, scripting (JavaScript, PDI’s built-in “User Defined Java Expression”), logging, clustering, and integration with Pentaho BI for reporting. Lineage and monitoring in Enterprise.
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

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.

Users can embed Java, JavaScript, or invoke external scripts. PDI’s open architecture allows custom plugins for new steps/connectors. The code is open-source, so full extensibility is available, though it requires Java development.
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
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.
Users can embed Java, JavaScript, or invoke external scripts. PDI’s open architecture allows custom plugins for new steps/connectors. The code is open-source, so full extensibility is available, though it requires Java development.
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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