Comparing Funnel with IBM DataStage 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 IBM DataStage
Pros
- Parallel processing engine for high-throughput ETL, optimized for large data volumes.
- Robust metadata management, data lineage, and governance via InfoSphere platform integration.
- Supports on-premise, virtualized, and containerized (Cloud Pak) deployments for flexibility.
- Extensive transformation library (data cleansing, lookups, joins) and connectivity (files, databases, mainframes, Hadoop).
Cons
- High total cost of ownership: perpetual licensing and specialized administration needed.
- User interface and development experience feel dated compared to modern cloud ETL tools.
- Steep learning curve for job optimization (partitioning, parallel directives) and advanced features.
IBM DataStage Overview:
What I like about IBM DataStage
DataStage excels at processing huge data volumes with parallelism and pushdown optimization. The metadata-driven approach makes lineage tracking and governance straightforward.
What I dislike about IBM DataStage
Licensing and maintenance costs are high, and the UI feels dated. Complex jobs require specialized knowledge to optimize performance.
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.
Funnel vs IBM DataStage: Ease of Use and User 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.
IBM DataStage
DataStage Designer provides a visual canvas to build ETL jobs, but the interface is relatively old-school. Job parameters, parallelism, and performance tuning require specialized training. Monitoring and debugging use InfoSphere consoles.
Funnel vs IBM DataStage: Pricing Transparency and 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.
IBM DataStage
DataStage has high licensing costs (perpetual + support) and often requires dedicated hardware. Best suited for large enterprises with extensive ETL needs; cost-prohibitive for small/medium businesses.
Funnel vs IBM DataStage: Comprehensive 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.
IBM DataStage
Features include: visual job design, parallel processing (MPP), pushdown optimization (offloading to DB/Hadoop), data quality integration, metadata-driven development, and enterprise governance. Also supports REST and mainframe data sources.
Funnel vs IBM DataStage: Flexibility and 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.
IBM DataStage
Custom logic can be written via routines (BASIC, Java, or Python) and embedded in jobs. DataStage can integrate with external schedulers (Control M) and monitoring tools. However, it’s not open-source, so feature evolution is tied to IBM’s roadmap.
Summary of Funnel vs IBM DataStage vs Weld
Weld | Funnel | IBM DataStage | |
---|---|---|---|
Connectors | 200++ | 500+ | 200+ |
Price | $99 / Unlimited usage | $1.08 / flexpoint per month | Enterprise licensing (custom quotes, usually six-figure annual) |
Free tier | No | Yes | No |
Location | EU | SE | Armonk, NY, USA (IBM HQ) |
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 | 4.2 |
Conclusion
You’re comparing Funnel, IBM DataStage, 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..
- IBM DataStage: features include: visual job design, parallel processing (mpp), pushdown optimization (offloading to db/hadoop), data quality integration, metadata-driven development, and enterprise governance. also supports rest and mainframe data sources. . datastage has high licensing costs (perpetual + support) and often requires dedicated hardware. best suited for large enterprises with extensive etl needs; cost-prohibitive for small/medium businesses. .
- 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..