What I like about IBM DataStage
“Best data integration tool on the market with a wide range of connectors and advanced data integration and quality features.”
You’re comparing IBM DataStage vs Skyvia vs Weld. Explore how they differ on connectors, pricing, and features.


Loved by data teams from around the world
| Weld | IBM DataStage | Skyvia | |
|---|---|---|---|
| Connectors | 200+ | 200+ | 70+ |
| Price | $99 / 5M Active Rows | Enterprise licensing (custom, usually six-figure annual) | Free (limited); paid plans from $15/month for 10k rows |
| Free tier | |||
| Location | EU | Armonk, NY, USA (IBM HQ) | San Francisco, CA, USA |
| Extract data (ETL) | |||
| Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL) | |||
| Transformations | |||
| AI Assistant | |||
| On-Premise | |||
| Orchestration | |||
| Lineage | |||
| Version control | |||
| Load to/from Excel | Yes (ODBC/flat files) | Yes (CSV/Excel imports) | |
| Load to/from Google Sheets | |||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4 | 4 |
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
Skyvia is a cloud-based data integration platform that lets users perform ETL, ELT, data replication, backup, and synchronization without coding. It supports over 190 data sources, including CRMs, marketing tools, cloud apps, and databases, and can load data into major cloud warehouses like Snowflake, BigQuery, Redshift, and Azure Synapse. With a browser-based interface, users can build and schedule data pipelines, automate workflows, and monitor tasks with detailed logging and alerts. Skyvia also offers backup and restore for cloud apps, visual SQL queries, and API publishing, making it a flexible, no-code solution for managing and integrating cloud data.

Fast, no-code setup for loading data from 70+ sources to warehouses or cloud DBs.
Handles incremental loads and can auto-detect schema changes for many sources.
Built-in data replication (one-way sync) and backup options for cloud data.
Free tier available (limited rows and sources) for basic usage.
No advanced transformation engine—only simple filters, mappings, and formula fields.
Pricing based on rows and connectors; high-volume loads can be costly.
Support and community resources are limited compared to major ETL vendors.
G2 Reviews:
“It just makes pulling Facebook Ads data into Snowflake so much smoother. The whole integration is pretty seamless: it's like we’ve got all our data in one spot now.”
“While Skyvia is powerful, sometimes more advanced transformation scenarios require workarounds or can't be fully implemented within the visual designer.”
Overview
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.
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
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:
“Weld is still limited to a certain number of integrations - although the team is super interested to hear if you need custom integrations.”




Side-by-side

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.

Skyvia’s wizard-driven UI guides users through connecting source and destination, selecting objects, and scheduling. For basic use cases, it’s extremely quick. Complex pipelines aren’t its focus.
Weld is highly praised for its user-friendly interface and intuitive design, which allows even users with minimal SQL experience to manage data workflows efficiently. This makes it an excellent choice for smaller data teams or businesses without extensive technical resources.
Side-by-side
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.
Skyvia’s wizard-driven UI guides users through connecting source and destination, selecting objects, and scheduling. For basic use cases, it’s extremely quick. Complex pipelines aren’t its focus.
Weld is highly praised for its user-friendly interface and intuitive design, which allows even users with minimal SQL experience to manage data workflows efficiently. This makes it an excellent choice for smaller data teams or businesses without extensive technical resources.
Side-by-side

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.

Free tier allows up to 5000 rows/day. Paid plans start at $15/month for 10k rows plus $15 per additional 10k rows. For large-scale or continuous replication, costs scale accordingly.
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.
Side-by-side
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.
Free tier allows up to 5000 rows/day. Paid plans start at $15/month for 10k rows plus $15 per additional 10k rows. For large-scale or continuous replication, costs scale accordingly.
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.
Side-by-side

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.

Supports: one-time or scheduled imports/exports, incremental loads (via key-based changes), data backup/restore, and firewall-friendly connectors. No transformations beyond mappings/filters.
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.
Side-by-side
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.
Supports: one-time or scheduled imports/exports, incremental loads (via key-based changes), data backup/restore, and firewall-friendly connectors. No transformations beyond mappings/filters.
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.
Side-by-side

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.

Users can define simple formulas for fields (e.g., concatenation). For advanced transformations, they need external tools (e.g., dbt) after loading. No support for scripting within ETL.
Weld offers advanced SQL modeling and transformations directly within its platform with the help of AI, providing users with unparalleled control and flexibility over their data. Leveraging its powerful AI capabilities, Weld automates repetitive tasks and optimizes data workflows, allowing teams to focus on getting value and insights. Additionally, Weld's custom connector framework enables users to build connectors to any API, making it easy to integrate new data sources and tailor data pipelines to meet specific business needs. This flexibility is particularly beneficial for teams looking to customize their data integration processes extensively and maximize the utility of their data without needing external tools.
Side-by-side
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.
Users can define simple formulas for fields (e.g., concatenation). For advanced transformations, they need external tools (e.g., dbt) after loading. No support for scripting within ETL.
Weld offers advanced SQL modeling and transformations directly within its platform with the help of AI, providing users with unparalleled control and flexibility over their data. Leveraging its powerful AI capabilities, Weld automates repetitive tasks and optimizes data workflows, allowing teams to focus on getting value and insights. Additionally, Weld's custom connector framework enables users to build connectors to any API, making it easy to integrate new data sources and tailor data pipelines to meet specific business needs. This flexibility is particularly beneficial for teams looking to customize their data integration processes extensively and maximize the utility of their data without needing external tools.
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