What I like about Rivery
“As a data analyst, I find the tool really easy to use; it's intuitive how you connect to the different data sources and create your data pipelines.”
You’re comparing Rivery vs Skyvia vs Weld. Explore how they differ on connectors, pricing, and features.


Loved by data teams from around the world
| Weld | Rivery | Skyvia | |
|---|---|---|---|
| Connectors | 200+ | 200+ | 70+ |
| Price | $99 / 5M Active Rows | $0.75 per credit *100MB of data replication | Free (limited); paid plans from $15/month for 10k rows |
| Free tier | |||
| Location | EU | US | 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 (CSV/Excel imports) | ||
| Load to/from Google Sheets | |||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4.7 | 4 |
Overview
Rivery is a SaaS-based ELT data integration platform designed to simplify the process of loading data from a wide variety of sources, including custom API-based platforms, into your preferred data warehouse. Although Rivery does not support real-time, on-the-fly data transformations during the loading process, it compensates with powerful post-load transformation capabilities. This allows users to clean, shape, and enrich their data after it has been ingested, ensuring the data is ready for analysis. Rivery’s user-friendly interface and automation features make it a strong option for teams looking to streamline their data workflows without heavy coding.

Supports custom integrations though native GUI
Has reverse ETL option
Supports Python
Has data transformation capabilities
Great customer support
Lack of advanced error handling features
Cannot transform data on the fly (ETL)
Complex pricing model
UI is lacking when working with larger complex pipelines
Product documentation is lacking
As a user on G2 puts it::
“As a data analyst, I find the tool really easy to use; it's intuitive how you connect to the different data sources and create your data pipelines.”
“For first-time users, it would be good to have some demo buttons; still, if you are familiar with terms, you'll manage to navigate between windows.”
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

Rivery is known for its ease of use, especially for data analysts who need to connect different data sources and create pipelines quickly. Its intuitive GUI makes setup straightforward.

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
Rivery is known for its ease of use, especially for data analysts who need to connect different data sources and create pipelines quickly. Its intuitive GUI makes setup straightforward.
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

Rivery's pricing is complex and based on credits, which may not be straightforward for all users. Costs can rise significantly with increased data usage.

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
Rivery's pricing is complex and based on credits, which may not be straightforward for all users. Costs can rise significantly with increased data usage.
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

The platform supports custom integrations, Python scripting, and reverse ETL, making it versatile for various data integration needs, but lacks on-the-fly transformation capabilities.

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
The platform supports custom integrations, Python scripting, and reverse ETL, making it versatile for various data integration needs, but lacks on-the-fly transformation capabilities.
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

Rivery offers flexibility in custom integrations and supports post-load transformations, but its user interface may lack robustness for managing larger, more complex pipelines.

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
Rivery offers flexibility in custom integrations and supports post-load transformations, but its user interface may lack robustness for managing larger, more complex pipelines.
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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