Comparing Dataddo with StreamSets Data Collector and Weld
Carolina Russ6 min read
What is Dataddo
Dataddo is a fully managed, no-code data integration platform designed for business users, marketers, and analysts who need quick access to data without engineering support. It supports over 300 prebuilt connectors to cloud apps, databases, and BI tools, and offers flexible data flows for ETL, ELT, reverse ETL, and dashboard integrations. If a specific connector isn’t available, Dataddo will build it on request. The platform emphasizes ease of use, with automated handling of API changes, built-in pipeline monitoring, and a “SmartCache” feature that temporarily stores historical data, allowing teams to run reports without immediately setting up a data warehouse. With support for secure data practices (SOC 2, ISO 27001, GDPR compliance) and simple, transparent pricing plans, including a free tier, Dataddo is ideal for organizations looking to centralize data quickly and with minimal overhead.
Pros
- No-code interface makes setup simple for non-technical users.
- Integrates with 300+ platforms, including many marketing and CRM tools.
- Onboarding and connector requests are generally well-handled.
- Offers competitive pricing, especially for small teams.
Cons
- Some users report delays for complex issues.
- New or niche sources may not be instantly available.
- Cancelling or modifying plans can be frustrating.
G2 Review:
What I like about Dataddo
It is so user friendly and doesnt have any learning curve. Any user can really understand and create their own custom flows without any external support
What I dislike about Dataddo
If a flow is created, Dataddo needs to introduce how to add more features in the flow (maybe edit columns or add/remove them instead of creating and replacing with a net new flow).
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
- 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
Cons
- 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:
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
Dataddo
Dataddo offers a clean, intuitive no-code interface that allows users to set up data flows quickly. The drag-and-drop flow builder and prebuilt connectors minimize the learning curve, making it accessible for non-technical users.
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
Dataddo
Pricing is straightforward and competitive, with plans starting at $99/month for three data flows. The free tier allows users to test the platform with limited functionality before committing to a paid plan.
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
Dataddo
Dataddo supports over 300 connectors, ETL/ELT workflows, reverse ETL capabilities, data transformations, and built-in monitoring.
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
Dataddo
While Dataddo is primarily designed for ease of use, it still offers flexibility through its wide range of connectors and the ability to create custom data flows. However, it may not provide the same level of customization as more technical platforms.
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 Dataddo vs StreamSets Data Collector vs Weld
| Weld | Dataddo | StreamSets Data Collector | |
|---|---|---|---|
| Connectors | 200+ | 398+ | 200+ |
| Price | $79 / 5M Active Rows | $99.00 / mo for 3 data flows to sync data between any source and destination | Data Collector: Free (OSS); Data Ops Platform: Custom enterprise pricing |
| Free tier | No | Yes | Yes |
| Location | EU | US/EU | San Francisco, CA, USA |
| Extract data (ETL) | Yes | Yes | Yes |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | Yes | No |
| Transformations | Yes | Yes | Yes |
| AI Assistant | Yes | No | No |
| On-Premise | No | No | Yes |
| Orchestration | Yes | Yes | Yes |
| Lineage | Yes | Yes | Yes |
| Version control | Yes | No | Yes |
| Load data to and from Excel | Yes | No | Yes |
| Load data to and from Google Sheets | Yes | Yes | No |
| Two-Way Sync | Yes | Yes | No |
| dbt Core Integration | Yes | No | No |
| dbt Cloud Integration | Yes | No | No |
| OpenAPI / Developer API | Yes | No | No |
| G2 Rating | 4.8 | 4.7 | 4.5 |
Conclusion
You’re comparing Dataddo, StreamSets Data Collector, Weld. Each of these tools has its own strengths:
- Dataddo: dataddo supports over 300 connectors, etl/elt workflows, reverse etl capabilities, data transformations, and built-in monitoring. . pricing is straightforward and competitive, with plans starting at $99/month for three data flows. the free tier allows users to test the platform with limited functionality before committing to a paid plan..
- 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 $79 for 5 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises..
