Comparing Fivetran with Stitch and Weld
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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
- Depends on external tools for data transformations (e.g., DBT)
- No built-in reverse ETL capabilities
- Complex and expensive pricing model
- Limited flexibility for data transformations
- No AI assistant or advanced automation features
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 Stitch
Pros
- Easy to setup and use
- A cost-friendly pricing model that's easy to understand and based on usage
- Integrates with Talend
- Includes transformations with JSON
- Fully managed no-code ELT data pipelines
Cons
- Require deep technical knowledge to get full value out of the platform
- The quality can vary a lot between different connectors as they are not maintained by Stitch
- Depends on the Singer open source framework which can break without notice
A reviewer on Gartner said::
What I like about Stitch
Stitch is an affordable tool for bringing data "as is" from the various data sources (Google Ads, Salesforce or even MySQL) to a data warehouse (Redshift, Snowflake, BigQuery, etc.)
What I dislike about Stitch
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.
Fivetran vs Stitch: Ease of Use and User Interface
Fivetran
While Fivetran offers a comprehensive set of connectors, it requires more technical knowledge, especially for setting up and managing data transformations, as it relies on external tools like DBT.
Stitch
Stitch is relatively easy to set up and use, offering no-code connectors and an affordable pricing model, but users may need deep technical knowledge to leverage its full potential.
Fivetran vs Stitch: Pricing Transparency and 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.
Stitch
Stitch's pricing model is cost-friendly and based on usage, making it accessible for many users. However, costs can increase if data volumes grow significantly.
Fivetran vs Stitch: Comprehensive Feature Set
Fivetran
Although Fivetran excels in ELT capabilities and offers near real-time data replication, it lacks built-in reverse ETL and advanced transformation features. Users must depend on third-party tools for data transformation, adding to the complexity and cost.
Stitch
Stitch offers fully managed no-code ELT data pipelines and integrates with Talend, but relies heavily on the Singer open-source framework, which can be less stable.
Fivetran vs Stitch: Flexibility and Customization
Fivetran
With Fivetran, the ability to transform data is more limited and often requires additional tools like DBT, which adds layers of complexity and can slow down the process for users who need quick and easy data manipulation.
Stitch
Stitch is designed for simplicity and ease of use, but customization is limited and dependent on the capabilities of the open-source Singer framework.
Summary of Fivetran vs Stitch vs Weld
| Weld | Fivetran | Stitch | |
|---|---|---|---|
| Connectors | 150+ | 500+ | 140+ |
| Price | $99 / 2 connectors | $1,052 / 2M Active Rows | $100 / 5M rows |
| Free tier | No | Yes | Yes |
| Extract data (ETL) | Yes | Yes | Yes |
| Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | No |
| 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 | 4.5 |
Conclusion
When comparing Fivetran and Weld, Weld emerges as a more cost-effective and efficient platform, particularly for businesses looking to save on operational costs and minimize the need for large data engineering teams. Weld offers all the capabilities of Fivetran, including ELT, data transformations, and reverse ETL, but with significantly less manpower required to manage and maintain data workflows. Weld’s all-in-one solution, enhanced by its advanced AI capabilities, automates repetitive tasks, optimizes data workflows, and reduces the need for extensive manual intervention. This automation not only streamlines processes but also cuts down on the high costs associated with managing large volumes of data and employing a large data engineering team. Furthermore, Weld's straightforward and affordable pricing model makes it an attractive option for companies aiming to manage their data more efficiently and economically. In contrast, Fivetran’s dependence on external tools for data transformation and its complex, volume-based pricing model can lead to higher expenses and greater resource demands, particularly for businesses that require extensive customization and control over their data workflows.
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