You’re comparing Adverity vs StreamSets Data Collector vs Weld. Explore how they differ on connectors, pricing, and features. 
Loved by data teams from around the world
| Weld | Adverity | StreamSets Data Collector | |
|---|---|---|---|
| Connectors | 200+ | 600+ | 200+ |
| Price | $99 / 5M Active Rows | $500 / month | Data Collector: Free (OSS); Data Ops Platform: Custom enterprise pricing |
| Free tier | |||
| Location | EU | IT | 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 | 4.5 | 4.5 |
Overview
Adverity is a standout data integration platform transforming siloed marketing data into actionable insights. With more than 600 marketing data connectors, it is designed for marketers to make better decisions and improve performance across all campaigns and channels.
Data extraction and loading
Flexibility and customization
Scalability
User-friendly interface
Unlimited data and connections
Expensive, especially for small businesses
Steep learning curve
Reporting capabilities could be improved
Initial setup complexity
Performance issues with large datasets
A reviewer on Capterra:
“Ease of use, various data connection points readily available for integration and extraction, ranging from Social platforms to various DSPs. Users can easily set up a frequent data update and even connect with other dashboards like Data Studio.”
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
Adverity offers a user-friendly interface but has a steeper learning curve due to its broad feature set, which might be overwhelming for beginners.
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
Adverity offers a user-friendly interface but has a steeper learning curve due to its broad feature set, which might be overwhelming for beginners.
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
Adverity’s pricing is on the higher side, especially for small businesses, which may find the cost prohibitive. It is ideal for larger enterprises that need extensive data integration capabilities.
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
Adverity’s pricing is on the higher side, especially for small businesses, which may find the cost prohibitive. It is ideal for larger enterprises that need extensive data integration capabilities.
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
Adverity supports a wide range of connectors and provides robust data extraction, transformation, and loading capabilities. However, the platform's comprehensive feature set can be a double-edged sword, offering great functionality but also requiring significant effort to master.
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
Adverity supports a wide range of connectors and provides robust data extraction, transformation, and loading capabilities. However, the platform's comprehensive feature set can be a double-edged sword, offering great functionality but also requiring significant effort to master.
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
Adverity is highly customizable, offering flexibility to adapt to various data needs and integration scenarios, making it a strong choice for businesses that require tailored data solutions.
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
Adverity is highly customizable, offering flexibility to adapt to various data needs and integration scenarios, making it a strong choice for businesses that require tailored data solutions.
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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