Boomi vs. Fivetran – Overview
About Boomi
Boomi Data Integration (formerly Rivery) is a cloud-native enterprise platform, which provides a unified solution for data ingestion, transformation, and workflow orchestration. The biggest differentiator is the completeness of Boomi’s offering, combining the ease-of-use of a no-code SaaS with the power and flexibility of a custom-coded solution.
About Fivetran
Fivetran is a managed extract and load tool that was created in 2012. Fivetran is headquartered in Oakland, California with offices around the world. They have a large customer base and are considered an easy-to-use choice for their ease of connection. Fivetran charges users on monthly active rows (MAR), which is the number of unique primary keys moved from source to target within one calendar month.
Boomi vs. Fivetran – Features
| Boomi | Fivetran | |
| Cloud-native and fully managed | Yes | Yes |
| Native connectors | 200+ | 500+ |
| Connect to any API Source | Yes | Not natively. Requires Cloud function. |
| Built-in workflow orchestration | Yes. Manage dependencies within and between pipelines with conditional logic, containers, loops and advanced scheduling. | No. Requires other tools to get the job done. |
| Built-in data transformation | Yes. SQL and Python. | No. Requires other tools to get the job done. |
| Reverse ETL | Yes. Push insights to any app. | No. Can’t sync data back to apps. |
| Built-in data model templates | Yes. Ready-made data model templates that unify multiple sources. | Siloed data model templates for single source only. |
| Database replication | Full table and incremental via change data capture or custom SQL for any unique replication logic. | Full table and incremental via change data capture or limited teleport snapshot dependent of a primary key. |
| Granular control over data replication | Yes. Including control over the destination schema, granularity and replication schedules. | Limited. |
| Support SLAs | Yes | Yes |
| Developer friendly | Yes. Multiple environments & built in deployment mode, version control, robust API & CLI. | API and version control for transformation only. |
| Multi-tenant support | Yes. Native environments with RBAC for each. | No. Requires separate accounts with management of each. |
| Security | HIPAA, GDPR, SOC 2, ISO 27001 | HIPAA, GDPR, SOC 2, ISO 27001, PCI |
| Pricing | Based on true data size or # runs. Differentiated for databases and apps for greater efficiency. | Based on rows (even if the rows have very few columns). |
Boomi vs. Fivetran – Product
Boomi
Boomi Data Integration — formerly Rivery — is the next-generation data platform built for the AI era.
Now part of the Boomi Enterprise Platform, Boomi Data Integration empowers organizations to build automated, end-to-end data pipelines that deliver trusted, governed, and near real-time data to analytics tools, AI models, and intelligent agents — all at scale.
From cloud data lakes to CRM, ERP, and bespoke SaaS applications, Boomi Data Integration gives your teams complete control and visibility over your data — so you can trust your data, move faster, and power your most ambitious AI and analytics initiatives.
Fivetran
Fivetran is an EL (extraction and load) tool, where the transformation component of the ETL/ELT process is only possible via 3rd party tools such as dbt or Coalesce.io.
Fivetran provides hundreds of native connectors with support for all main databases and data warehouses as targets. More than half of Fivetran’s connectors are Lite connectors built for a specific use case and with limited end-points support. Custom connectors are possible with Fivetran, but they must be coded via 3rd party Cloud Functions, which are then called by Fivetran. These Cloud Functions come at an additional cost to run and require maintenance. Building and maintaining custom connectors in-house and outside of Fivetran can be done to handle custom data needs outside of Fivetran’s capabilities.
Boomi vs. Fivetran – Pricing
Boomi
Boomi Data Integration offers both on-demand (pay-as-you-go) pricing and annual contracts. All plans—Base, Professional, Pro Plus, and Enterprise—are available with either model.
Pricing is based on a credit system using Boomi Data Units (BDUs), formerly called RPUs.
Database, file storage, and webhook sources are priced by data volume transferred.
Application/API sources are priced by pipeline execution, with an option to shift to volume-based pricing for high-frequency syncs.
Boomi does not charge based on:
- Number of connectors or integrations
- Number of API executions or database tables
- Row count or sync frequency
All Boomi Data Integration plans include:
- Access to 200+ fully managed connectors
- Reverse ETL
- Change Data Capture (CDC) capabilities
- Support for both standard and high-frequency API replication
- Flexible, consumption-based pricing across all use cases
Learn more about Boomi Data Integration pricing on Boomi’s pricing page or contact sales to explore enterprise agreements.
Fivetran
Fivetran’s pricing is consumption based. Their pricing model is controlled by monthly active rows (MAR), which is the number of unique primary keys moved from source to target within one calendar month. For some use cases this can make Fivetran’s pricing high and difficult to estimate (i.e. when the target schema generated by Fivetran may include include multiple tables impact by a single change in the data source hence generating multiple MARs for the same change).
Fivetran model is changing as of March 2025 with the biggest change being MARs counted per connector and not across all connectors.
Boomi vs. Fivetran – Support
Boomi
Boomi offers 24/7 global support as well as onboarding services and dedicated customer success services, which vary by plan. Support is engineering-led and solutions focused.
Boomi’s Gartner Peer Insights user rating for quality of support is 4.6/5, with an overall score of 4.8/5.
Fivetran
Fivetran offers support through in-platform support tickets as well as the option to purchase premium support.
Fivetran’s Gartner Peer Insights user rating for quality of support is 4.5/5 with an overall score of 4.6/5.
Boomi vs. Fivetran – Summary
Fivetran
Fivetran is a good option for teams looking for an easy-to-use data integration tool. If you are looking to implement an end-to-end ETL/ELT solution you’ll have to pair Fivetran with other tools. For example, you’ll need to leverage different tools like, dbt for transformation, Airflow for orchestration, and Hightouch or Census for reverse ETL.
Key benefits when evaluating Fivetran include:
- Ease of connection
- ERD/normalized schemas for each SaaS solution
- Embedded dbt Core with custom dbt models
Limitations of Fivetran as an ETL/ELT tool include:
- No proprietary transformation capabilities
- Custom connectors need to be built and maintained via Cloud Functions
- No automation of data pipelines promotion from dev to prod
- No reverse ETL capabilities
- No orchestration capabilities
Boomi
Boomi is an end-to-end platform rather than just an extract and load tool, like Fivetran. Boomi offers data orchestration, data transformation, and reverse ETL capabilities for every plan out of the box. This enables data teams to simplify their data stack and achieve more with fewer tools.
In regards to data transformation, Boomi offers ETLT processes, where you can complete in-flight transformations of data using Boomi’s industry-first Python integration as well as push-down SQL transformations or integration with dbt.
For users looking for enterprise-ready solutions, Boomi comes with a number of developer capabilities, including:
- Built-in Boomi version history management
- Context-sensitive variables
- Multiple environments
- Metadata collection
- Audit logging
When evaluating connectors and customizability, Boomi offers a simple custom connector to connect to any API source without the need for an external cloud function. Fivetran connections are tied to their best practices as it pertains to datasets, which in certain use cases could create connection inflexibility and additional downstream transformation work.
Finally, Boomi’s differentiated pricing model between replication of database data vs. API-source data, generates greater savings for data teams.