You’re comparing Weld vs IBM DataStage vs Talend. Explore how they differ on connectors, pricing, and features. 
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| Feature | Weld | IBM DataStage | Talend |
|---|---|---|---|
| Core Platform | |||
| Price | $79 / 5M Active Rows | Enterprise licensing (custom, usually six-figure annual) | Custom price, volume based |
| Free tier | No | No | No |
| Location | DK, (EU) | US | US |
| Connectors & Sync | |||
| Connectors | 200+ | 200+ | 100+ |
| Extract data (ETL) | Yes | Yes | Yes |
| Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL) | Yes | No | No |
| Two-Way Sync | Yes | No | No |
| Transformations & AI | |||
| Transformations | Yes | Yes | Yes |
| AI Assistant | Yes | No | No |
| dbt Core Integration | Yes | No | No |
| dbt Cloud Integration | Yes | No | No |
| Governance & DevOps | |||
| Orchestration | Yes | Yes | Yes |
| Lineage | Yes | Yes | Yes |
| Version control | Yes | Yes | Yes |
| On-Premise | No | Yes | Yes |
| OpenAPI / Developer API | Yes | No | Yes |
| Integrations | |||
| Load to/from Excel | Yes | Yes | No |
| Load to/from Google Sheets | Yes | No | No |
| Ratings | |||
| G2 rating | 4.8 | 4 | 4 |
Overview
Weld is a unified ELT and data activation platform that combines ingestion, modeling, transformations, orchestration, lineage, and reverse ETL in a single SaaS interface. With premium in-house–built connectors, an intuitive UI, and near real-time syncs, Weld enables both technical and non-technical users to create and manage data workflows efficiently. Weld also includes an AI assistant to support SQL modeling, generate transformations, and streamline repetitive tasks. Teams can ingest data from a wide range of sources—including marketing platforms, CRMs, databases, Google Sheets, Excel, and APIs—into their cloud data warehouse and activate it back into business tools.
Lineage, orchestration, and workflow features included by default
Handles large datasets and near real-time data sync
ELT and reverse ETL in one platform
User-friendly interface with minimal setup required
Flat, predictable monthly pricing model
200+ in-house–built, high-quality connectors
AI assistant for modeling and transformations
Some SQL knowledge is useful for advanced modeling
Optimized for cloud-warehouse workflows (Snowflake, BigQuery, Redshift, etc.)
Feature set is streamlined for modern ELT/activation use cases
A reviewer on G2 said:
Overview
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.
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).
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.
G2 Reviews:
“Best data integration tool on the market with a wide range of connectors and advanced data integration and quality features.”
“I quite like the platform as a whole, but I believe it can improve regarding data lineage (it should indeed improve now with the arrival of Manta to the IBM portfolio).”
Overview
Talend is now part of Qlik and forms the foundation of the Qlik Talend Data Integration and Data Quality suite. The platform includes Talend Data Fabric and Qlik Talend Cloud, offering data integration, data quality, governance, application integration, and API management. It supports both ETL and ELT patterns and provides deployment flexibility across cloud, on-premise, and hybrid environments. Talend is generally positioned for larger or more mature data teams that need broad capabilities rather than a simple plug-and-play pipeline tool.
Large set of enterprise-grade connectors and integration patterns
Supports ETL, ELT, APIs, and real-time pipelines
Strong data quality and governance capabilities
Flexible deployment: cloud, hybrid, and on-premise
Advanced features suitable for complex enterprise environments
Complex and harder to use for non-technical users
Pricing is custom and often expensive for smaller teams
Implementation can require significant setup and ongoing maintenance
More capabilities than needed for simple or mid-market workflows
As a reviewer on Gartner states: :
“We are satisfied with Qlik Talend cloud, it enabled for us a seamless data integration and transformation, thanks to the tight integration with Qlik Cloud analytics.”
“It's a very good tool however this tool is better for data migration and a little lacking/ or difficult to use when it comes to some cleansing or further analysis.”
Side-by-side
Weld’s interface is built for clarity and speed, enabling users with varying levels of technical experience to manage data pipelines and models efficiently. Its built-in lineage and orchestration tools provide transparency across workflows.
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.
Talend has a steep learning curve, especially for non-technical users, due to its extensive feature set and advanced capabilities, which require significant training and experience to utilize fully.
Side-by-side
Weld’s interface is built for clarity and speed, enabling users with varying levels of technical experience to manage data pipelines and models efficiently. Its built-in lineage and orchestration tools provide transparency across workflows.
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.
Talend has a steep learning curve, especially for non-technical users, due to its extensive feature set and advanced capabilities, which require significant training and experience to utilize fully.
Side-by-side
Weld offers a simple and predictable pricing model starting at $79 for 5 million active rows. This flat, usage-transparent structure makes budgeting straightforward for small and medium-sized teams.
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.
Talend's pricing is custom and can be expensive, especially for small businesses. It requires a substantial upfront investment, making it more suitable for large enterprises with significant data needs.
Side-by-side
Weld offers a simple and predictable pricing model starting at $79 for 5 million active rows. This flat, usage-transparent structure makes budgeting straightforward for small and medium-sized teams.
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.
Talend's pricing is custom and can be expensive, especially for small businesses. It requires a substantial upfront investment, making it more suitable for large enterprises with significant data needs.
Side-by-side
Weld provides ELT ingestion, SQL-based transformations, reverse ETL activation, data lineage, orchestration, and workflow management in a single platform. Its AI assistant accelerates modeling and transformation tasks.
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.
Talend offers a robust feature set with a large number of connectors, supporting both ELT and ETL capabilities, along with options for on-premise deployments. It is well-suited for mature data teams needing comprehensive data integration and management.
Side-by-side
Weld provides ELT ingestion, SQL-based transformations, reverse ETL activation, data lineage, orchestration, and workflow management in a single platform. Its AI assistant accelerates modeling and transformation tasks.
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.
Talend offers a robust feature set with a large number of connectors, supporting both ELT and ETL capabilities, along with options for on-premise deployments. It is well-suited for mature data teams needing comprehensive data integration and management.
Side-by-side
Users can model data using SQL enhanced by Weld’s AI assistant, automate workflows, and build custom connectors to any API. This provides strong flexibility for teams that want to tailor integrations and transformations within one platform.
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.
Talend provides flexibility and customization options, making it ideal for large enterprises with complex data needs. However, this comes at the cost of ease of use, particularly for less experienced users.
Side-by-side
Users can model data using SQL enhanced by Weld’s AI assistant, automate workflows, and build custom connectors to any API. This provides strong flexibility for teams that want to tailor integrations and transformations within one platform.
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.
Talend provides flexibility and customization options, making it ideal for large enterprises with complex data needs. However, this comes at the cost of ease of use, particularly for less experienced users.
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CUSTOMER STORIES
“One of the biggest impacts has been unlocking new ways to buy media. Before, we didn’t have the data to back up strategic decisions – now we do.”
“Before Weld, we had to rely on custom Python scripts and manual processes that were time-consuming and error-prone.”
“We’re still a team of three, but we’re often doing far more than the equivalent of three full-time employees. That’s down to how we're able to leverage systems, data, and processes.”
“We’ve always been a KPI-driven company. But we wanted to scale that mindset across every team member, every team, every decision.”
“Before Weld, our data infrastructure was limited and we relied heavily on Excel files and custom Python scripts.”
“Weld has saved us a ton of time, from not having data ready to having a fully functional data warehouse and connectors.”
“By integrating Weld, Amazon S3, and Databricks, Soundboks built a modern data pipeline that automates data ingestion, improves reporting, and provides up-to-date visibility into sales performance”
“We didn’t have a good data setup, so we lacked the business insights we needed. Weld has allowed us to set up a structured data infrastructure and access insights quickly.”
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