10 Things to Keep in Mind When You Migrate From Fivetran

Key takeaways

Here’s what to consider when migrating from Fivetran.

• Map your Fivetran data, including sources, destinations, and transformations.
• Select a platform considering your team’s needs and goals.
• Ensure continuity with backups and phased rollouts.
• Document schema and transformation changes to prevent disruptions.
• Run parallel pipelines and validate outputs with checks and tests.
• Cut over during low-traffic windows with rollback options.
• Review pricing and plan for scalable costs.
• Prioritize key connectors and validate completeness.
• Train your team and assign clear roles.
• Monitor and retire Fivetran once the new setup stabilizes.

Many teams turn to Fivetran for its simplicity. It promises a quick setup, automated pipelines, and less engineering overhead. Initially, it all works well.

Over time, challenges begin to surface. Costs climb unpredictably with MAR-based billing, and transformation options feel limited. That’s when most teams start planning for migration.

However, migrating away from Fivetran is not just swapping one tool for another. This represents a strategic shift that impacts budgets, operations, and long-term trust in data.

A rushed move can cause downtime, high costs, or lost data. Hence, this guide covers the 10 things to keep in mind while you plan to migrate from Fivetran so your transition is smooth and future-proof.

What do you like best about Fivetran? Fivetran truly simplifies the process of connecting and syncing data across systems. Its out-of-the-box connectors are very robust, requiring minimal setup and almost no ongoing maintenance. I especially appreciate the automated schema management and the reliability of the pipelines — once configured, they just work without needing babysitting. What do you dislike about Fivetran? The pricing model can become expensive at scale, especially when dealing with large volumes of data or many connectors. Also, while the platform supports a wide variety of connectors, customization beyond standard transformations sometimes feels limited without moving into external tools like dbt.

Verified User

10 Things to Keep in Mind While You Plan to Migrate from Fivetran

Data migration success depends on thorough planning. If you plan to migrate from FIvetran soon, here are the key points to consider.

1. Assess your current data architecture and requirements

Before moving away from Fivetran, take a step back and map out your entire setup. Start with your data sources. List every SaaS tool, database, event stream, and file system that feeds into your pipelines. Identify who owns each source, the data volume you handle, and how you access it. This will tell you which integrations may require extra attention.

Don’t forget the destinations. Note whether you use a warehouse like Snowflake or BigQuery, a lake like S3, or a mix of both. Record sync frequencies, latency requirements, and the costs tied to storage or compute.

Finally, check your ETL or ELT processes. Document where transformations run, from dbt models to warehouse SQL. Include orchestration tools, compliance needs, and business-critical dashboards. A clear baseline highlights dependencies, risks, and requirements, giving you the confidence to plan migration.

2. Choose the right alternative platform

There can’t be one perfect data integration tool for all teams. The right Fivetran alternative tends to your specific requirements and struggles.

If you want open-source flexibility and cloud data pipeline automation in one tool, Airbyte is worth considering. It offers over 600 connectors with active community support. It is an ideal choice for teams that already have a development team since it requires more technical knowledge.

Similarly, Estuary is known for its real-time sync capabilities. It has more than 200 connectors and delivers sub-second change data capture with exactly-once guarantees. It is ideal for streaming or high-frequency updates.

If you want SQL-focused heavy transformations, Matillion is one of the strongest contenders. It integrates deeply with 150+ connectors. However, its consumption-based pricing can become expensive for heavy workloads.

Hevo combines the pricing predictability, simplicity, and transformation flexibility. It offers a no-code setup with over 150 connectors, real-time and batch sync, and transparent pricing. This balance of usability and cost control makes it compelling for growing companies.

Want to compare two top platforms side by side? Check out our detailed Hevo vs Fivetran comparison article.

3. Plan for data continuity and backup strategy

Data loss during migration can disrupt months of analysis. Ensure reliable backups across all pipelines and destinations. Cloud snapshots, warehouse exports, and versioned storage are a reliable safety net for unexpected pipeline issues.

Begin with less critical connectors to test how the new data migration tool handles syncs and transformations. This small-scale rollout will help you identify issues without risking business-critical data.

Once the initial phase runs without errors, expand gradually to higher-priority sources. Design an overlap period where both platforms run simultaneously, and document clear recovery steps in case of failure.

4. Handle schema mapping and transformation challenges

Fivetran applies its own conventions, such as prefixing Salesforce tables with ‘sf_’ and standardizing field names. These schema differences can cause major disruptions if left unchecked.

The platform also handles data types differently. For example, JSON structures might be flattened in Fivetran but preserved elsewhere. These shifts affect transformations, dbt models, and downstream reporting.

You can manage this by documenting the table and field mapping before cutover. Include business context, not just technical names. Back it up with automated tests for schema validation so inconsistencies surface before they affect production.

5. Develop a comprehensive testing strategy

While you run both pipelines in parallel, compare their outputs in a controlled environment. This prevents testing from interfering with production. Confirm accuracy by checking row counts, checksums, and business rules across the two platforms.

Test how the new setup handles stress. Simulate data spikes, concurrent sync jobs, and API rate limits to identify bottlenecks. Run load tests against your data warehouse to ensure it can handle the processing volume.

Automate reconciliation wherever possible. Add SQL-based checks for row parity, schema consistency, and null constraints. Schedule regular reports and set up alerts for a well-monitored cutover.

6. Plan your cutover strategy carefully

A well-timed cutover can be the difference between a well-designed migration and a data disruption. Instead of cutting off all connectors at once, do it gradually in phases. Start small with less critical connectors like development databases or backup systems. Use these early wins to refine your process before moving to revenue-critical pipelines.

Schedule migrations during low-traffic windows to reduce the impact on business users.  Weekends or scheduled maintenance windows often give you extra recovery time. Establish rollback procedures if data quality issues arise. Monitor performance closely for the first 48 to 72 hours of migration and assign a team to handle urgent fixes.

7. Address cost optimization and pricing models

Fivetran’s pricing can surge unexpectedly, especially since Monthly Active Rows are now calculated per connection, instead of across an account. Ensure that you understand the new tool’s pricing structure thoroughly.

Compare connector-based billing and volume or event models to decide which fits your roadmap and workloads. Estimate how costs scale as your data volume grows. Include subscription fees, implementation costs, training, and running parallel pipelines during migration when both tools are live.

Negotiate terms that work within your budget. Consider asking the new vendor for usage caps, predictable escalation, or committed-use discounts on annual contracts. Look for opportunities to combine batch loading for historical data with real-time syncs only where business impact demands it.

8. Prepare for connector migration and validation

Critical connections, such as NetSuite, Shopify, HubSpot, and Klaviyo, require special focus since they directly affect revenue and operations. Confirm that the new tool fully supports these integrations and matches the functionality you rely on currently. Some tools may not cover every field, transformation, or webhook, so be sure to document the gaps.

Re-create authentication configurations with secure handling of API keys, OAuth tokens, and credentials. Test data completeness by comparing record counts, custom fields, and freshness across systems.

You might need to rewrite scripts for custom processes that previously depended on Fivetran’s API to maintain workflow integrity. Keep a reference guide of connector-specific differences to ensure data pipeline automation as your infrastructure scales.

9. Plan team training and change management

A migration is only successful if your team can work confidently with the new platform. Identify the skill gaps between your current setup and the new tool. If you are moving to a more complex ETL platform, focus training on areas where your team needs the most support.

Prioritize hands-on training with real company data instead of general examples. Create environments that mirror production so your team can practice adding connectors, resolving errors, and running checks without risk.

Assign owners to each task and set timelines to avoid confusion. Productivity may dip during the transition, so factor in learning curves in your timeline. Support the team with clear documentation, reference guides, and experts or vendor contacts who can step in when needed.

10. Implement post-migration monitoring and optimization

Finishing the migration is only the first step. The real value comes from how well you monitor and improve the new platform over time. Dashboards allow you to monitor pipeline reliability, sync performance, data freshness, and cost metrics.

Ensure data quality with automated checks and business rules, and compare outcomes against pre-migration benchmarks for consistency and accuracy. Set up alerting thresholds for critical issues and establish clear escalation procedures.

But don’t retire Fivetran just yet. Keep it running in parallel for at least two to three weeks until you have confidence in the new setup. Use monitoring insights to identify optimization opportunities, such as adjusting sync frequencies, consolidating similar connectors, or implementing efficient transformation logic for ongoing cost and performance improvements.

All these best practices will stabilize your migration and lay the foundation for a modern data architecture that scales with your business.

Why Consider Hevo Data as Your Fivetran Alternative?

Hevo matches Fivetran’s simplicity while adding the flexibility and performance that growing teams need.

It supports both real-time streaming and batch processing to ensure freshness in time-critical use cases. It’s built to scale as data volumes grow, so it simply adapts to your workflow.

Hevo’s 150+ pre-built connectors make it simple to integrate SaaS tools, databases, and warehouses, with an option to request or create custom connectors. For advanced workflows, Hevo supports Python scripting, dbt models, and GUI-based transformations.

Pricing is event-based, starting at $239 per month, so you can plan costs without worrying about surprise billing. Additionally, Hevo provides strong error handling and automatic schema drift management.

Hevo’s enterprise-grade features, such as HIPAA compliance, SOC 2 certification, and dedicated support, provide you with the confidence to scale operations effectively.

Build scalable, no-code data pipelines with Hevo → Book a demo.

FAQs

Sarthak Bhardwaj Customer Experience Engineer, Hevo

Sarthak is a skilled professional with over 2 years of hands-on experience in JDBC, MongoDB, REST API, and AWS. His expertise has been instrumental in driving Hevo's success, where he excels in adept problem-solving and superior issue management. Sarthak's technical proficiency and strategic approach have consistently contributed to optimizing operations and ensuring seamless performance, making him a vital asset to the team.