What I like about Matillion
“Built-in connectors to heaps of systems; ability to create custom connectors; active community and quick responses to forum questions”
You’re comparing Matillion vs StreamSets Data Collector vs Weld. Explore how they differ on connectors, pricing, and features.


Loved by data teams from around the world
| Weld | Matillion | StreamSets Data Collector | |
|---|---|---|---|
| Connectors | 200+ | 110+ | 200+ |
| Price | $99 / 5M Active Rows | $2.00 per credit | Data Collector: Free (OSS); Data Ops Platform: Custom enterprise pricing |
| Free tier | |||
| Location | EU | UK | San Francisco, 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 | Yes (via file connectors) | ||
| Load to/from Google Sheets | |||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4.3 | 4.5 |
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
StreamSets Data Collector is an open-source data integration engine built for continuous ingestion, transformation, and delivery—often referred to as a DataOps platform. It supports both streaming (Kafka, Kinesis) and batch (JDBC, files) data sources, with a drag-and-drop canvas to design pipelines. The standout feature is Schema Drift Detection: pipelines automatically adapt to changes in incoming data schemas. Commercial editions add operational monitoring, metadata management, and lineage.

Schema Drift Detection automatically adjusts to incoming data changes, preventing many pipeline breaks.
Supports both streaming (Kafka, Kinesis, JMS) and batch (JDBC, files) in the same pipeline.
Drag-and-drop pipeline builder with over 200 connectors and transformation processors.
Open-source core (Data Collector); enterprise edition adds operational monitoring, lineage, and governance.
Open-source lacks robust monitoring and lineage features; must pay for the Data Ops Platform for full enterprise functionality.
UI performance can degrade for very large pipelines; memory usage can be significant.
Steep learning curve for advanced pipeline patterns, especially around custom scripting in Groovy or Java.
StreamSets Data Operations Platform:
“StreamSets’ ability to automatically detect and adapt to schema changes (drift) in streaming sources greatly reduces pipeline failures.”
“The open-source feature set is limited—monitoring, lineage, and enterprise support require the paid Data Ops Platform. Debugging complex pipelines can be tricky if not familiar with the UI.”
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

Matillion has a steep learning curve, especially for non-technical users, due to its robust feature set and advanced capabilities designed for larger enterprises.

The Data Collector UI is a canvas where users drag origin, processor, and destination stages. Schema drift is highlighted automatically. While basic pipelines are easy to build, complex transformations may require custom scripting in Groovy/Java.
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
Matillion has a steep learning curve, especially for non-technical users, due to its robust feature set and advanced capabilities designed for larger enterprises.
The Data Collector UI is a canvas where users drag origin, processor, and destination stages. Schema drift is highlighted automatically. While basic pipelines are easy to build, complex transformations may require custom scripting in Groovy/Java.
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

Matillion's pricing can be expensive, particularly for small businesses, as it is based on credits and requires a significant upfront investment.

Data Collector is free, but enterprise features (monitoring, lineage, role-based access) require paid Data Ops Platform licenses. Pricing is custom based on number of nodes and connectors.
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
Matillion's pricing can be expensive, particularly for small businesses, as it is based on credits and requires a significant upfront investment.
Data Collector is free, but enterprise features (monitoring, lineage, role-based access) require paid Data Ops Platform licenses. Pricing is custom based on number of nodes and connectors.
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

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.

Features: streaming & batch pipelines, schema drift detection, transformation processors (masking, joins, lookups), origin/destination connectors (Kafka, S3, HDFS, JDBC), and enterprise ops (alerting, lineage, governance) in paid edition.
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
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.
Features: streaming & batch pipelines, schema drift detection, transformation processors (masking, joins, lookups), origin/destination connectors (Kafka, S3, HDFS, JDBC), and enterprise ops (alerting, lineage, governance) in paid edition.
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

Matillion provides extensive customization and flexibility options, particularly for large enterprises, but may be overkill for smaller teams or simpler use cases.

Supports custom processors in Groovy/Java for bespoke logic. Pipelines can be parameterized and deployed in containers or VMs. Integration with external schedulers (Airflow) and monitoring tools (Prometheus, Grafana).
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
Matillion provides extensive customization and flexibility options, particularly for large enterprises, but may be overkill for smaller teams or simpler use cases.
Supports custom processors in Groovy/Java for bespoke logic. Pipelines can be parameterized and deployed in containers or VMs. Integration with external schedulers (Airflow) and monitoring tools (Prometheus, Grafana).
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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