Comparing Etlworks Integrator with IBM DataStage 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 IBM DataStage
IBM DataStage (part of IBM InfoSphere Information Server) is a high-performance ETL and data integration platform that supports parallel processing and massive data volumes. It provides a visual design interface (DataStage Designer) to build data flows, along with features for metadata management, data lineage, and enterprise governance. DataStage can run on-premise or on cloud (via IBM Cloud Pak for Data) and integrates with IBM’s data quality and master data management solutions.
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
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.
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.
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.
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.
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.
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.
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.
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 Etlworks Integrator vs IBM DataStage vs Weld
| Weld | Etlworks Integrator | IBM DataStage | |
|---|---|---|---|
| Connectors | 200+ | 300+ | 200+ |
| Price | $79 / No data volume limits | Credit-based (e.g., $0.10/credit; volume discounts available) | Enterprise licensing (custom quotes, usually six-figure annual) |
| Free tier | No | Yes | No |
| Location | EU | Pittsburgh, PA, USA | 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 | 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 | 4.2 |
Conclusion
You’re comparing Etlworks Integrator, IBM DataStage, 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. .
- 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..
