You’re comparing Google Cloud Dataflow vs Matillion vs Weld. Explore how they differ on connectors, pricing, and features. 
Loved by data teams from around the world
| Weld | Google Cloud Dataflow | Matillion | |
|---|---|---|---|
| Connectors | 200+ | 30+ | 110+ |
| Price | $99 / 5M Active Rows | Per vCPU-second ($0.0106/vCPU-minute) + RAM and storage; streaming pipelines incur additional costs | $2.00 per credit |
| Free tier | |||
| Location | EU | GCP Global (multi-region) | UK |
| 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 | ||
| Load to/from Google Sheets | |||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4.5 | 4.3 |
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
Matillion is a cloud-native data integration platform that enables enterprises to build and manage ETL/ELT pipelines using a low-code, visual interface. Designed for cloud data warehouses like Snowflake, Redshift, and BigQuery, it allows users to extract, transform, and load data from various sources efficiently. With strong scheduling, orchestration, and monitoring features, Matillion is well-suited for handling complex workflows and large-scale data transformation needs.
Large number of connectors
Robust feature set
Lots of advanced features for larger enterprises and data teams
Has both ELT and ETL capabilities
On premise options
Expensive for small businesses
Steep learning curve for non-technical users
Requires a large upfront investment and implementation
A reviewer on G2 said::
“Built-in connectors to heaps of systems; ability to create custom connectors; active community and quick responses to forum questions”
“Some components are a bit clunky; cloud version is not mature and lacks some features from the server-based version”
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.
Matillion has a steep learning curve, especially for non-technical users, due to its robust feature set and advanced capabilities designed for larger enterprises.
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.
Matillion has a steep learning curve, especially for non-technical users, due to its robust feature set and advanced capabilities designed for larger enterprises.
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.
Matillion's pricing can be expensive, particularly for small businesses, as it is based on credits and requires a significant upfront investment.
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.
Matillion's pricing can be expensive, particularly for small businesses, as it is based on credits and requires a significant upfront investment.
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.
Matillion offers a robust set of features with support for both ETL and ELT, along with numerous connectors and on-premise options, making it ideal for large enterprises with complex data needs.
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.
Matillion offers a robust set of features with support for both ETL and ELT, along with numerous connectors and on-premise options, making it ideal for large enterprises with complex data needs.
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.
Matillion provides extensive customization and flexibility options, particularly for large enterprises, but may be overkill for smaller teams or simpler use cases.
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.
Matillion provides extensive customization and flexibility options, particularly for large enterprises, but may be overkill for smaller teams or simpler use cases.
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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