Comparing Airbyte with Rivery and Weld
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What is Airbyte
Pros
- Open-source platform
- A really large number of connectors and destinations
- Easy deployment
- Managed cloud option
- Engineering-focused with advanced options to build your own connectors and features
- Has both ELT and Reverse ETL options
- Large community
Cons
- More suited for advanced teams
- Require more maintenance
- The quality of connectors can vary because of open-source
- High dependence on community
In a review from Confessions of a Data Guy, he shares::
What I like about Airbyte
If you don't have workloads that currently use DBT or fit well into that model, this probably isn’t the tool for you.
What I dislike about Airbyte
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.
Airbyte vs Rivery: Ease of Use and User Interface
Airbyte
Airbyte is an open-source platform that is easier for teams with strong coding skills but may be challenging for those without technical expertise, especially when building custom connectors.
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.
Airbyte vs Rivery: Pricing Transparency and Affordability
Airbyte
Airbyte offers a flexible pricing model based on credits, but costs can add up depending on data volume, making it more suitable for teams that can optimize their usage.
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.
Airbyte vs Rivery: Comprehensive Feature Set
Airbyte
The platform supports a large number of connectors and destinations and is designed to work well with DBT and SQL, providing robust options for teams building a modern data stack.
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.
Airbyte vs Rivery: Flexibility and Customization
Airbyte
Airbyte's open-source nature and customization options make it highly flexible for teams with the capability to maintain and build on the platform, but this flexibility comes with a higher maintenance burden.
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 Airbyte vs Rivery vs Weld
Weld | Airbyte | Rivery | |
---|---|---|---|
Connectors | 150+ | 350+ | 200+ |
Price | $99 / 2 connectors | $2.50/credit (one million rows = 6 credits; 1 GB = 4 credits) | $0.75 per credit *100MB of data replication |
Free tier | No | Yes | Yes |
Extract data (ETL) | Yes | Yes | Yes |
Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | Yes | Yes |
Version control | Yes | No | No |
Orchestration | Yes | No | No |
Lineage | Yes | No | No |
AI Assistant | 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 |
G2 Rating | 4.8 | 4.2 | 4.7 |
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