Comparing Fivetran with Rivery and Weld


What is Fivetran
Pros
- Wide variety of connectors
- Easy setup, low maintenance, and scalability with pre-built connectors
- Robust security protocols
- Detailed and helpful documentation
- Near real-time replication capabilities
Cons
- Complex and expensive pricing model
- Depends on external tools for data transformations (e.g., DBT)
- Doesn't support data transformations pre-load
- No AI assistant or advanced automation features
- Steep learning curve for DBT beginners
From a review on G2:
What I like about Fivetran
The pre-built connectors makes data integration super easy, without the need of an expensive data engineering team. If you are using DBT, there is a DBT package for most of the pre-built connectors that will provide configurable data marts/models.
What I dislike about Fivetran
New connectors are released infrequently, and pricing is somewhat opaque if you are not familiar. It is somewhat opinionated, so if you are not already using a modern data stack w. their preferred partners it's a bit harder to integrate.
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.
Feature-by-Feature Comparison
Ease of Use & Interface
Fivetran
While Fivetran offers a comprehensive set of connectors, it requires more technical knowledge, especially for setting up and managing advanced data transformations, as it may rely on external tools like DBT. In other words, Fivetran is easy to use for data ingestion, but transformations demand proficiency with SQL or DBT.
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.
Pricing & Affordability
Fivetran
Fivetran’s pricing can be quite complex and increases significantly with the volume of data, making it potentially expensive for growing companies or those with large datasets. This can be a disadvantage for teams looking for a cost-effective solution.
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.
Feature Set
Fivetran
Although Fivetran excels in ELT capabilities and offers near real-time data replication, it lacks advanced transformation features. Users must rely on DBT for advanced transformations, which introduces complexity but does not require a third-party platform if DBT Core is used.
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.
Flexibility & Customization
Fivetran
Fivetran relies on SQL-based transformations via DBT Core, which gives users power and flexibility but may not suit those needing quick, low-code manipulation.
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 Fivetran vs Rivery vs Weld
Weld | Fivetran | Rivery | |
---|---|---|---|
Connectors | 200+ | 700+ | 200+ |
Price | $79 / No data volume limits | Usage-based, starting $500 for 1 million MARs (no fixed base) | $0.75 per credit *100MB of data replication |
Free tier | No | Yes | Yes |
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 | No | Yes |
AI Assistant | Yes | No | No |
On-Premise | No | No | No |
Orchestration | Yes | Yes | No |
Lineage | Yes | Yes | No |
Version control | Yes | No | No |
Load data to and from Excel | Yes | Yes | No |
Load data to and from Google Sheets | Yes | Yes | No |
Two-Way Sync | Yes | No | No |
dbt Core Integration | Yes | Yes | No |
dbt Cloud Integration | Yes | Yes | No |
OpenAPI / Developer API | Yes | Yes | Yes |
G2 Rating | 4.8 | 4.2 | 4.7 |
Conclusion
You’re comparing Fivetran, Rivery, Weld. Each of these tools has its own strengths:
- Fivetran: although fivetran excels in elt capabilities and offers near real-time data replication, it lacks advanced transformation features. users must rely on dbt for advanced transformations, which introduces complexity but does not require a third-party platform if dbt core is used.. fivetran’s pricing can be quite complex and increases significantly with the volume of data, making it potentially expensive for growing companies or those with large datasets. this can be a disadvantage for teams looking for a cost-effective solution..
- 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..