Comparing Funnel with StreamSets Data Collector and Weld


What is Funnel
Pros
- Great interface
- Requires little technical expertise
- Straightforward dashboard
- More than 500 data connectors
- Great onboarding and training
Cons
- Expensive and complex, especially for smaller businesses
- Limited advanced analytics
- Reporting features could be more robust
- Limited to marketing use cases
- Steep and long learning curve
A reviewer on G2:
What I like about Funnel
We use Funnel mostly for ingesting data into BigQuery. Using the native connectors is significantly more efficient than building a direct connection to the relevant APIs, particularly for Facebook / Meta data.
What I dislike about Funnel
Recently the price of the platform has gone up. Although it is still priced competitively vs its alternatives.
What is StreamSets Data Collector
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
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
Funnel
Funnel.io is designed to be easy to use, with a straightforward dashboard that requires little technical expertise, making it accessible for marketers.
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
Funnel
Funnel.io's pricing can be complex and expensive, especially for smaller businesses, which might find it challenging to justify the cost for their needs. The platform operates on a flexpoints system, a type of consumption-based pricing, which can make it difficult for users to predict their monthly costs accurately.
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
Funnel
The platform offers over 500 data connectors and great onboarding and training, but its analytics capabilities may be limited for users needing more advanced features.
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
Funnel
Funnel.io is limited to marketing use cases and may lack the flexibility needed for more comprehensive data operations, but is effective within its niche.
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 Funnel vs StreamSets Data Collector vs Weld
Weld | Funnel | StreamSets Data Collector | |
---|---|---|---|
Connectors | 200+ | 500+ | 200+ |
Price | $79 / No data volume limits | $1.08 / flexpoint per month | Data Collector: Free (OSS); Data Ops Platform: Custom enterprise pricing |
Free tier | No | Yes | Yes |
Location | EU | SE | 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 | Yes | No |
On-Premise | No | No | Yes |
Orchestration | Yes | No | Yes |
Lineage | Yes | No | Yes |
Version control | Yes | No | Yes |
Load data to and from Excel | Yes | No | Yes |
Load data to and from Google Sheets | Yes | No | No |
Two-Way Sync | Yes | No | No |
dbt Core Integration | Yes | No | No |
dbt Cloud Integration | Yes | No | No |
OpenAPI / Developer API | Yes | No | No |
G2 Rating | 4.8 | 4.5 | 4.5 |
Conclusion
You’re comparing Funnel, StreamSets Data Collector, Weld. Each of these tools has its own strengths:
- Funnel: the platform offers over 500 data connectors and great onboarding and training, but its analytics capabilities may be limited for users needing more advanced features.. funnel.io's pricing can be complex and expensive, especially for smaller businesses, which might find it challenging to justify the cost for their needs. the platform operates on a flexpoints system, a type of consumption-based pricing, which can make it difficult for users to predict their monthly costs accurately..
- 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..