Comparing Fivetran with Segment 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 Segment
Pros
- Real-time data integration capabilities
- Pre-built and maintained connectors for popular data sources
- Has advanced features for managing customer data
- Easy to setup and use
Cons
- Quickly becomes very expensive
- Not suitable for only use for ELT
- Heavily skewed toward sales and marketing platforms
- Custom integration or customization is really hard to do
A reviewer on G2 said::
What I like about Segment
Segment connects to all the various platforms that we're using which makes it very easy to send data around. No engineering needed.
What I dislike about Segment
Pricing could be a bit more affordable, especially if you want to use ETL processes.
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
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.
Segment
Segment is easy to set up and use, offering real-time data integration and advanced features for managing customer data, making it a great choice for businesses focusing on customer data platforms.
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.
Segment
Segment can quickly become very expensive, especially for smaller businesses, due to its pricing model based on the number of visitors and advanced features.
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.
Segment
The platform provides robust real-time data integration capabilities and is heavily skewed towards sales and marketing platforms, making it ideal for businesses with a strong focus on customer data.
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.
Segment
Segment offers limited flexibility for use outside of customer data and event tracking, with customization options that can be challenging for more complex requirements.
Summary of Fivetran vs Segment vs Weld
| Weld | Fivetran | Segment | |
|---|---|---|---|
| Connectors | 200+ | 700+ | 300+ |
| Price | $79 / 5M Active Rows | Usage-based, starting $500 for 1 million MARs (no fixed base) | $120/month 10,000 visitors |
| 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 | No |
| 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 | Yes |
| dbt Cloud Integration | Yes | Yes | No |
| OpenAPI / Developer API | Yes | Yes | Yes |
| G2 Rating | 4.8 | 4.2 | 4.6 |
Conclusion
You’re comparing Fivetran, Segment, 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..
- Segment: the platform provides robust real-time data integration capabilities and is heavily skewed towards sales and marketing platforms, making it ideal for businesses with a strong focus on customer data.. segment can quickly become very expensive, especially for smaller businesses, due to its pricing model based on the number of visitors and advanced features..
- 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..