Comparing Rivery with Talend and Weld


What is Rivery
Pros
- Supports custom integrations though native GUI
- Has reverse ETL option
- Supports Python
- Has data transformation capabilities
- Great customer support
Cons
- 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::
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.
What I dislike about Rivery
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.
What is Talend
Pros
- Large number of connectors
- Robust feature set
- Lots of advanced features for larger enterprises and data teams
- Has both ELT and ETL capabilities
- On premise options
Cons
- Expensive for small businesses
- Steep learning curve for non-technical users
- Requires a large upfront investment and implementation
As a reviewer on Gartner states: :
What I like about Talend
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.
What I dislike about Talend
Is 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.
What is Weld
Pros
- 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
Cons
- 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:
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
Rivery
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.
Talend
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.
Pricing & Affordability
Rivery
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.
Talend
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.
Feature Set
Rivery
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.
Talend
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.
Flexibility & Customization
Rivery
Rivery offers flexibility in custom integrations and supports post-load transformations, but its user interface may lack robustness for managing larger, more complex pipelines.
Talend
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.
Summary of Rivery vs Talend vs Weld
| Weld | Rivery | Talend | |
|---|---|---|---|
| Connectors | 200+ | 200+ | 100+ |
| Price | $79 / 5M Active Rows | $0.75 per credit *100MB of data replication | Custom price |
| Free tier | No | Yes | No |
| Location | EU | US | US |
| Extract data (ETL) | Yes | Yes | Yes |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | Yes | Yes |
| Transformations | Yes | Yes | Yes |
| AI Assistant | Yes | No | 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 | No |
| 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 | Yes | No |
| G2 Rating | 4.8 | 4.7 | 4 |
Conclusion
You’re comparing Rivery, Talend, Weld. Each of these tools has its own strengths:
- Rivery: 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.. 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..
- Talend: 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.. 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..
- 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 $79 for 5 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises..