Comparing Hevo with Rivery and Weld



What is Hevo
Pros
- Supports both ELT, ELT, and reserve ELT
- Plenty of fully maintained connectors
- Great for non-technical users
- Simple UI that's easy to work with
- Affordable pricing
Cons
- Limited features for more advanced use cases
- Limited custom scheduling features
- Only 50 connectors are available on the Free plan
- Lack of flexibility when wanting to edit pipelines
- Error messages and status codes could be better
As one reviewer on G2 puts it: :
What I like about Hevo
Hevo is really good for normal pipelines, but it has some limitations for more complex use cases.
What I dislike about Hevo
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
What is Weld
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.
Hevo vs Rivery: Ease of Use and User Interface
Hevo
Hevo is designed with non-technical users in mind, offering a simple UI and code-free capabilities, making it easy for beginners to use.
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.
Hevo vs Rivery: Pricing Transparency and Affordability
Hevo
Hevo offers affordable pricing and a free plan with limited connectors, making it accessible for startups and small businesses. However, the costs can rise with data volume and feature needs.
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.
Hevo vs Rivery: Comprehensive Feature Set
Hevo
Hevo supports ETL, ELT, and reverse-ETL, making it versatile for different data needs. It also has plenty of fully maintained connectors, although it may lack some advanced features required by seasoned data professionals.
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.
Hevo vs Rivery: Flexibility and Customization
Hevo
While Hevo is great for non-technical users, it lacks flexibility and customization options for more complex data tasks, making it less suitable for advanced data teams.
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.
Summary of Hevo vs Rivery vs Weld
Weld | Hevo | Rivery | |
---|---|---|---|
Connectors | 200++ | 150+ | 200+ |
Price | €99 / Unlimited usage | €299 / 5M rows | €0.75 per credit *100MB of data replication |
Free tier | No | Yes | Yes |
Location | EU | INDIA | 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 | No |
Orchestration | Yes | No | No |
Lineage | Yes | No | No |
Version control | Yes | No | No |
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 | Yes | No |
dbt Cloud Integration | Yes | No | No |
OpenAPI / Developer API | Yes | Yes | Yes |
G2 Rating | 4.8 | 4.3 | 4.7 |
Conclusion
You’re comparing Hevo, Rivery, Weld. Each of these tools has its own strengths:
- Hevo: hevo supports etl, elt, and reverse-etl, making it versatile for different data needs. it also has plenty of fully maintained connectors, although it may lack some advanced features required by seasoned data professionals.. hevo offers affordable pricing and a free plan with limited connectors, making it accessible for startups and small businesses. however, the costs can rise with data volume and feature needs..
- 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..
- 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..