What I like about Etlworks Integrator
“Etlworks Integrator’s breadth of connectors and flexible transformation engine (SQL/JavaScript) let us integrate data from dozens of sources quickly.”
You’re comparing Etlworks Integrator vs Rivery vs Weld. Explore how they differ on connectors, pricing, and features.


Loved by data teams from around the world
| Weld | Etlworks Integrator | Rivery | |
|---|---|---|---|
| Connectors | 200+ | 300+ | 200+ |
| Price | $99 / 5M Active Rows | Credit-based (e.g., $0.10/credit; volume discounts available) | $0.75 per credit *100MB of data replication |
| Free tier | |||
| Location | EU | Pittsburgh, PA, USA | US |
| 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 | Yes (Google Sheets) | ||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4.5 | 4.7 |
Overview
Etlworks Integrator is a cloud-based ETL platform that provides over 300 connectors (databases, SaaS, files, big data) and a visual interface to build complex data flows. It can run both batch and streaming pipelines, support transformations via SQL or JavaScript, and integrate with Kafka, Snowflake, Redshift, Google BigQuery, and more. It also offers features for data replication, CDC, and workflow orchestration.

300+ connectors for databases, cloud storage, SaaS apps, and streaming platforms.
Supports both batch and streaming (CDC) with configurable schedules and triggers.
Transformations via SQL, JavaScript, or built-in functions; data validation and error-handling features.
Cloud-based with on-prem runtime options for connecting to internal resources securely.
UI complexity: designing flows with many steps can be difficult to navigate.
Subscription is credit-based (e.g., $0.10/credit), making cost estimation tricky for variable workloads.
Less brand recognition and community support compared to leading ETL tools.
Etlworks Integrator Features:
“Etlworks Integrator’s breadth of connectors and flexible transformation engine (SQL/JavaScript) let us integrate data from dozens of sources quickly.”
“The UI can be overwhelming for beginners, and pricing (credit-based) can be hard to predict for varying workloads.”
Overview
Rivery is a SaaS-based ELT data integration platform designed to simplify the process of loading data from a wide variety of sources, including custom API-based platforms, into your preferred data warehouse. Although Rivery does not support real-time, on-the-fly data transformations during the loading process, it compensates with powerful post-load transformation capabilities. This allows users to clean, shape, and enrich their data after it has been ingested, ensuring the data is ready for analysis. Rivery’s user-friendly interface and automation features make it a strong option for teams looking to streamline their data workflows without heavy coding.

Supports custom integrations though native GUI
Has reverse ETL option
Supports Python
Has data transformation capabilities
Great customer support
Lack of advanced error handling features
Cannot transform data on the fly (ETL)
Complex pricing model
UI is lacking when working with larger complex pipelines
Product documentation is lacking
As a user on G2 puts it::
“As a data analyst, I find the tool really easy to use; it's intuitive how you connect to the different data sources and create your data pipelines.”
“For first-time users, it would be good to have some demo buttons; still, if you are familiar with terms, you'll manage to navigate between windows.”
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

Etlworks Integrator’s Flow Designer uses a canvas with source, transformation, and destination steps. While powerful and flexible, the interface has a steep learning curve; nested steps and branching can become difficult to visualize.

Rivery is known for its ease of use, especially for data analysts who need to connect different data sources and create pipelines quickly. Its intuitive GUI makes setup straightforward.
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
Etlworks Integrator’s Flow Designer uses a canvas with source, transformation, and destination steps. While powerful and flexible, the interface has a steep learning curve; nested steps and branching can become difficult to visualize.
Rivery is known for its ease of use, especially for data analysts who need to connect different data sources and create pipelines quickly. Its intuitive GUI makes setup straightforward.
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 are based on credits consumed by data volume and transformations. Free trial provides limited credits. For predictable workloads, budget forecasting requires careful usage analysis.

Rivery's pricing is complex and based on credits, which may not be straightforward for all users. Costs can rise significantly with increased data usage.
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 are based on credits consumed by data volume and transformations. Free trial provides limited credits. For predictable workloads, budget forecasting requires careful usage analysis.
Rivery's pricing is complex and based on credits, which may not be straightforward for all users. Costs can rise significantly with increased data usage.
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: 300+ connectors, CDC replication, batch/streaming pipelines, SQL/JavaScript transformations, error handling, scheduling, and secure on-prem gateways. Also supports webhooks and REST API triggers.

The platform supports custom integrations, Python scripting, and reverse ETL, making it versatile for various data integration needs, but lacks on-the-fly transformation capabilities.
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: 300+ connectors, CDC replication, batch/streaming pipelines, SQL/JavaScript transformations, error handling, scheduling, and secure on-prem gateways. Also supports webhooks and REST API triggers.
The platform supports custom integrations, Python scripting, and reverse ETL, making it versatile for various data integration needs, but lacks on-the-fly transformation capabilities.
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

Supports embedding custom JavaScript or calling external services within pipelines. Can deploy integration nodes on-premise to access internal networks. Pipelines can be exported/imported for version control.

Rivery offers flexibility in custom integrations and supports post-load transformations, but its user interface may lack robustness for managing larger, more complex pipelines.
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
Supports embedding custom JavaScript or calling external services within pipelines. Can deploy integration nodes on-premise to access internal networks. Pipelines can be exported/imported for version control.
Rivery offers flexibility in custom integrations and supports post-load transformations, but its user interface may lack robustness for managing larger, more complex pipelines.
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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