Comparing Etlworks Integrator with StreamSets Data Collector and Weld
Carolina Russ6 min read
What is Etlworks Integrator
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.
Pros
- 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.
Cons
- 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:
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.
What I dislike about Etlworks Integrator
The UI can be overwhelming for beginners, and pricing (credit-based) can be hard to predict for varying workloads.
What is StreamSets Data Collector
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.
Pros
- 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.
Cons
- 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:
What I like about StreamSets Data Collector
StreamSets’ ability to automatically detect and adapt to schema changes (drift) in streaming sources greatly reduces pipeline failures.
What I dislike about StreamSets Data Collector
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.
What is Weld
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.
Pros
- Premium quality connectors and reliability
- User-friendly and easy to set up
- AI assistant
- Very competitive and easy-to-understand pricing model
- Reverse ETL option
- Lineage, orchestration, and workflow features
- Advanced transformation and SQL modeling capabilities
- Ability to handle large datasets and near real-time data sync
- Combines data from a wide range of sources for a single source of truth
Cons
- Requires some technical knowledge around data warehousing and SQL
- Limited features for advanced data teams
A reviewer on G2 said:
What I like about Weld
First and foremost, Weld is incredibly user-friendly. The graphical interface is intuitive, which makes it easy to build data workflows quickly and efficiently. Even with little experience in SQL and pipeline management, we found that Weld was straightforward and easy to use. What really impressed me, however, was Weld's flexibility. It was able to handle data from a wide variety of sources, including SQL databases, Google Sheets, and even APIs. The solution also allowed us to customize my data transformations in a way that best suited my needs. Whether I needed to clean data, join tables, or aggregate data, Weld had the necessary tools to accomplish the task. Weld's performance was also exceptional. I was able to run large-scale ETL jobs quickly and efficiently, with minimal downtime via a Snowflake instance and visualization via own-hosted Metabase. The solution's scalability meant that I could process more data without any issues. Another standout feature of Weld was its support. I never felt lost or unsure about how to use a particular feature, as the support team was always quick to respond to any questions or concerns that I had. Overall, I highly recommend Weld as an ETL solution. Its user-friendliness, flexibility, performance, and support make it an excellent choice for anyone looking to streamline their data integration processes. I will definitely be using Weld for all my ETL needs going forward.
What I dislike about Weld
Weld is still limited to a certain number of integrations - although the team is super interested to hear if you need custom integrations.
Feature-by-Feature Comparison
Ease of Use & Interface
Etlworks Integrator
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.
StreamSets Data Collector
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.
Pricing & Affordability
Etlworks Integrator
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.
StreamSets Data Collector
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.
Feature Set
Etlworks Integrator
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.
StreamSets Data Collector
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.
Flexibility & Customization
Etlworks Integrator
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.
StreamSets Data Collector
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).
Summary of Etlworks Integrator vs StreamSets Data Collector vs Weld
| Weld | Etlworks Integrator | StreamSets Data Collector | |
|---|---|---|---|
| Connectors | 200+ | 300+ | 200+ |
| Price | $79 / No data volume limits | Credit-based (e.g., $0.10/credit; volume discounts available) | Data Collector: Free (OSS); Data Ops Platform: Custom enterprise pricing |
| Free tier | No | Yes | Yes |
| Location | EU | Pittsburgh, PA, USA | San Francisco, CA, USA |
| Extract data (ETL) | Yes | Yes | Yes |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | No |
| Transformations | Yes | Yes | Yes |
| AI Assistant | Yes | No | No |
| On-Premise | No | Yes | Yes |
| Orchestration | Yes | Yes | Yes |
| Lineage | Yes | No | Yes |
| Version control | Yes | No | Yes |
| Load data to and from Excel | Yes | Yes | Yes |
| Load data to and from Google Sheets | Yes | Yes | No |
| Two-Way Sync | Yes | No | No |
| dbt Core Integration | Yes | No | No |
| dbt Cloud Integration | Yes | No | No |
| OpenAPI / Developer API | Yes | Yes | No |
| G2 Rating | 4.8 | 4.5 | 4.5 |
Conclusion
You’re comparing Etlworks Integrator, StreamSets Data Collector, Weld. Each of these tools has its own strengths:
- Etlworks Integrator: 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. . 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. .
- StreamSets Data Collector: 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. . 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: 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.. weld offers a straightforward and competitive pricing model, starting at $99 for 2 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises..
