Rivery vs. Fivetran: Top differences explained

Modern data teams can’t afford delays, rework, or unreliable pipelines. The right data integration platform minimizes effort and maximizes time to value — but not all solutions are built for long-term growth.

Choosing the right tool directly affects your team’s efficiency and your ability to deliver insights at scale. In this guide, we’ll compare Rivery versus Fivetran across key metrics like reliability, automation, and total cost of ownership.

What is Fivetran?

Fivetran is a fully managed data movement platform designed to make data access simple and reliable. You can easily automate the extraction and loading of data from over 700 sources into any major cloud data warehouse, lake, or analytical destination. 

The platform is built on a core philosophy of zero-maintenance, self-healing pipelines that automatically adapt to changes in source APIs and schemas. That means your team can focus on generating value from data rather than constantly fixing broken data pipelines.

At an enterprise scale, Fivetran handles over 9.1 petabytes (9100 terabytes) of data and 156 million pipeline syncs every month. By focusing exclusively on data movement and integration with industry-standard data transformation tools like dbt, Fivetran prioritizes depth over breadth. 

This focus on specialization is why companies like Okta have saved over 1,000 engineering hours and why Dropbox was able to cut its data ingestion and reporting time from eight weeks to just 30 minutes.

What is Rivery?

Rivery, acquired by Boomi in December 2024, is a cloud-native SaaS platform that provides an end-to-end solution for data integration. It combines several tools into one, offering data ingestion, transformation, workflow orchestration, and reverse ETL. With a library of 200 pre-built connectors and a no-code interface, Rivery aims to provide a single environment for managing the entire data lifecycle.

Rivery is best for teams consolidating their data stack and managing all pipeline activities in a single spot. However, this wide range of functionality also means the responsibility for configuring, managing, and maintaining these complex components falls into the hands of the user — a common challenge with Fivetran alternatives.

6 differences between Rivery and Fivetran

While both platforms move data, here’s how the different design philosophies translate to real-world outcomes in terms of maintenance, cost, and reliability.

1. Deployment and architecture

Fivetran offers a fully managed SaaS platform you can deploy in a hybrid model, allowing enterprise customers to run the service within their own cloud environment (AWS, GCP, or Azure) to meet compliance requirements. You get the data governance benefits of an on-premise data center without the infrastructure management.

Rivery is a standard cloud-native SaaS application. While it supports multiple environments for development and staging, it doesn’t offer the same level of deployment flexibility for enterprises in highly regulated industries.

Fivetran is built as a specialized, high-availability service for data movement, while Rivery is more of a broader workflow engine. 

2. Ease of use and automation

If ease of use matters most to you, Fivetran is engineered for zero-maintenance automation. Once a connector is configured — a process that typically takes minutes — the pipeline is self-healing and will automatically adapt to source API changes. 

That’s a non-trivial task that Fivetran handles over 22 million times a month for its customers without any manual intervention. It’s designed to eliminate the amount of engineering time teams waste on maintenance. 

Rivery’s offerings come at the cost of a steeper learning curve and more hands-on management. Its conditional logic and custom scripting require technical expertise to configure and maintain. While this control is valuable for unique and complex use cases, it places a significant amount of responsibility on the user.

3. Flexibility and customization

Rivery’s strength is its built-in flexibility. It provides a custom API connector builder and native Python support, allowing for intricate data processing. Fivetran favors extensibility through best-of-breed integrations. 

Instead of a proprietary scripting environment, Fivetran provides a Connector SDK and a robust REST API. These, respectively, enable the rapid construction of custom connectors running on Fivetran’s infrastructure (and architecture) as well as scalable, granular, programmatic control over data integration.

4. Support for transformations

Rivery has built-in SQL and Python transformations. This creates a tightly integrated experience, but it runs counter to the modern, best-of-breed data stack philosophy. 

Fivetran integrates seamlessly with the tools your data team likely already uses. It offers several options, including Quickstart Data Models for no-code transformations with dbt Core and dbt Cloud. By using the industry-standard dbt, Fivetran users benefit from a massive open-source community and an easy-to-use development workflow.

5. Ecosystem and integrations

Each missing connector is a custom development project for your team. Choosing a tool with the right integrations from the start will help you save time and money down the road. Fivetran leads the industry with over 700 fully managed connectors, compared to only around 200 from Rivery.  

This 3.5x difference dramatically reduces the chance your team will need to build and maintain a custom pipeline. Fivetran’s philosophy is clear: be the most reliable data movement component within a broader ecosystem of data integration tools. 

Our Fivetran competitor comparisons for Stitch, Airbyte, Matillion, and Talend can help you evaluate how connector depth affects your long-term scalability.

6. Pricing

Rivery’s pricing uses a credit-based system that can be confusing to predict. Fivetran uses a transparent, consumption-based model based on Monthly Active Rows (MAR), plus a generous free tier. 

But the sticker price isn’t the full story — metric data leaders need to look at the total cost of ownership. A platform that seems cheaper might require 10–20 extra engineering hours per week, making it far more expensive in the end. 

How to choose the best tool for your organization

The best way to choose the right platform is to look at your priorities. 

Choose Fivetran if you prioritize:

• Reliability and uptime: You need mission-critical data infrastructure with a 99.9% uptime SLA.
• Zero-maintenance automation: You want to free your engineers from pipeline maintenance and bug fixing. 
• Total cost of ownership: You know engineering time is your most valuable resource, and you want your team focused on the highest leverage tasks that can’t be automated.
• Best-of-breed architecture: You prefer specialized, industry-leading tools that provide everything you need (and more). 

Choose Rivery if you prioritize:

• End-to-end control: You want a single platform for ingestion, transformation, and orchestration.
• Complex, custom workflows: You have unique use cases that require extra programming and conditional logic.
• In-house expertise: Your team has the skill and time to manage a flexible platform.

Why is Fivetran the best ETL platform for you?

The best data integration tools work quietly and independently in the background, freeing your team to focus on creating value. 

Through automation, reliability, and scalability, Fivetran delivers a lower total cost of ownership and a faster path to insights. With its deep support for data transformations and extensibility management, Fivetran provides a fully automated service that eliminates the maintenance tax on your data team. 

Ready to get started? Sign up now to try Fivetran for free for 14 days.

FAQs

What does Fivetran specialize in?

Fivetran specializes in fully automated data movement, providing a zero-maintenance service for extracting data from over 700 sources and loading it into modern cloud data platforms. This allows Fivetran to deliver an industry-leading 99.9% uptime and handle the complexities of API and schema changes automatically.

How does Fivetran work?

Fivetran uses a library of pre-built, fully managed connectors to automatically extract data from your chosen sources. Once configured, it syncs data at your desired frequency and loads it into your destination in a normalized, analytics-ready format. Its self-healing architecture detects and resolves issues like API changes or schema drift without manual intervention.

Does Fivetran support data transformation?

Yes, Fivetran integrates seamlessly with industry-standard transformation tools. It offers Quickstart Data Models for no-code transformations and provides native, fully orchestrated integrations with both dbt Core and dbt Cloud. This best-of-breed approach allows data teams to use the most powerful and popular ETL tools on the market as part of a unified, automated ELT workflow. 

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