You’re comparing Google Cloud Dataflow vs Informatica Cloud vs Weld. Explore how they differ on connectors, pricing, and features. 
Loved by data teams from around the world
| Weld | Google Cloud Dataflow | Informatica Cloud | |
|---|---|---|---|
| Connectors | 200+ | 30+ | 200+ |
| Price | $99 / 5M Active Rows | Per vCPU-second ($0.0106/vCPU-minute) + RAM and storage; streaming pipelines incur additional costs | Subscription-based (custom quotes); typically starts ~$20k/year for base ETL usage |
| Free tier | |||
| Location | EU | GCP Global (multi-region) | Redwood City, CA, USA |
| Extract data (ETL) | |||
| Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL) | |||
| Transformations | |||
| AI Assistant | |||
| On-Premise | |||
| Orchestration | |||
| Lineage | |||
| Version control | |||
| Load to/from Excel | Via CSV in Cloud Storage | Yes (flat-file connectors) | |
| Load to/from Google Sheets | Yes (Google Sheets connector) | ||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4.5 | 4.4 |
Overview
Google Cloud Dataflow is a fully managed stream and batch processing service based on Apache Beam. It enables users to write ETL pipelines in Java or Python, which Dataflow executes on Google’s serverless infrastructure with autoscaling. It integrates natively with Pub/Sub, BigQuery, Cloud Storage, and other GCP services for end-to-end data processing.
Unified batch + streaming model via Apache Beam SDK (Java/Python).
Serverless autoscaling with dynamic work rebalancing for cost and performance optimization.
First-class integration with GCP services: Pub/Sub, BigQuery I/O connectors, Cloud Storage, Spanner, etc.
Built-in exactly-once processing semantics and windowing capabilities for streaming ETL.
Steep learning curve if unfamiliar with Apache Beam’s abstractions (PCollections, DoFns, pipelines).
Monitoring and debugging streaming pipelines can be complex—metrics and logs often require cross-referencing.
Cost can rise quickly for large-scale streaming (billed per vCPU-second and memory). Efficient pipeline tuning is critical.
G2 Reviews:
“Google cloud dataflow is automatically optimize and manages resources for you this platform supports multiple programming languages including Python, java and SQL and makes it easy for developers to focus on writing codes”
“It is costly as compared to other solutions”
Overview
Informatica Intelligent Cloud Services (IICS) is a cloud-native iPaaS that provides ETL/ELT, application integration, API management, and data quality in a single SaaS platform. It offers hundreds of pre-built connectors for SaaS apps, cloud databases, and on-premises systems via Secure Agents. Key features include drag-and-drop flow designer, real-time integrations, and monitoring dashboards.
Hundreds of SaaS, cloud DB, and on-prem connectors via a lightweight Secure Agent.
Unified services: ETL/ELT, data quality, API integration, and B2B/EDI flows.
Low-code, drag-and-drop interface for rapid flow development; pre-built templates accelerate common integrations.
Hybrid integration capability: connect cloud and on-prem data sources securely via Secure Agents.
Pricing can be difficult to estimate—charges apply per environment, per connector, data volume, and usage of additional services.
Performance throttling on large bulk loads; premium packaging is needed for high-throughput scenarios.
Learning curve for advanced features: API Designer, Data Quality transformations, and complex flow orchestration.
G2 reviews:
“Some of the standout aspects include: User Friendly Interface,Scalability and Cloud-Native Architecture, Automation and Scheduling.”
“Informatica CDI is quite expensive when compared to other cloud-based data integration tools, particularly for smaller organizations and teams.”
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
Dataflow pipelines are defined programmatically in Java or Python (Apache Beam). There is no drag-and-drop UI; developers use the Cloud Console or CLI to monitor, but pipeline creation and debugging happen in code and SDKs.
The IICS web UI provides a unified workspace where users build mappings and tasks using drag-and-drop. Pre-built templates simplify common use cases, but advanced features (e.g., data quality) require additional learning.
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
Dataflow pipelines are defined programmatically in Java or Python (Apache Beam). There is no drag-and-drop UI; developers use the Cloud Console or CLI to monitor, but pipeline creation and debugging happen in code and SDKs.
The IICS web UI provides a unified workspace where users build mappings and tasks using drag-and-drop. Pre-built templates simplify common use cases, but advanced features (e.g., data quality) require additional learning.
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
Charges for each pipeline based on vCPU-second, memory, and persistent disk usage. Streaming jobs are billed continuously. Without careful optimization (autoscaling, batching), costs can escalate. However, for high-throughput workloads, serverless autoscaling can be cost-effective versus self-managed clusters.
Informatica Cloud’s pricing includes a base license fee plus charges per connector, environment, and data usage. Small teams may find entry costs high, but larger enterprises benefit from consolidated integration and data services.
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
Charges for each pipeline based on vCPU-second, memory, and persistent disk usage. Streaming jobs are billed continuously. Without careful optimization (autoscaling, batching), costs can escalate. However, for high-throughput workloads, serverless autoscaling can be cost-effective versus self-managed clusters.
Informatica Cloud’s pricing includes a base license fee plus charges per connector, environment, and data usage. Small teams may find entry costs high, but larger enterprises benefit from consolidated integration and data services.
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 include: Batch & streaming unified model, windowing & triggers, exactly-once semantics, dynamic work rebalancing, and data-driven autoscaling. Supports FlexRS (spot pricing for batch) and integration with Dataflow SQL for SQL-based pipelines.
Key features: ETL/ELT mappings, real-time integrations, API & application integration, data quality, data masking, and B2B/EDI flows. It also includes monitoring dashboards, alerts, and SLA management.
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 include: Batch & streaming unified model, windowing & triggers, exactly-once semantics, dynamic work rebalancing, and data-driven autoscaling. Supports FlexRS (spot pricing for batch) and integration with Dataflow SQL for SQL-based pipelines.
Key features: ETL/ELT mappings, real-time integrations, API & application integration, data quality, data masking, and B2B/EDI flows. It also includes monitoring dashboards, alerts, and SLA management.
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 write custom transforms (ParDo, Map, GroupBy), can integrate UDFs, and use side inputs. Complex workloads requiring custom logic (stateful processing, custom connectors) are fully supported via Beam SDK. Cloud features like VPC, IAM, and KMS integrate security.
Users can create custom connectors via REST/SOAP or use the Generic Connector. Secure Agents allow on-premise integration. Mapping Designer supports custom transformations via Java or Groovy.
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 write custom transforms (ParDo, Map, GroupBy), can integrate UDFs, and use side inputs. Complex workloads requiring custom logic (stateful processing, custom connectors) are fully supported via Beam SDK. Cloud features like VPC, IAM, and KMS integrate security.
Users can create custom connectors via REST/SOAP or use the Generic Connector. Secure Agents allow on-premise integration. Mapping Designer supports custom transformations via Java or Groovy.
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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