A Step-by-Step Guide on How to Safely Migrate Away from Fivetran

Moving off a core ingestion tool like Fivetran can feel like open-heart surgery on your data pipelines and downstream reporting. Pipelines can break, timelines can stretch, and the reports your business relies on can go stale.

Still, many teams are making the move. In recent conversations with our sales team, companies looking to leave Fivetran keep giving the same reason: unpredictable MAR pricing.

The hard part is that most Fivetran users are mid-market or enterprise companies with dozens of connectors and established pipelines. The platform you move to has to support every one of those connectors. It also has to replicate the configurations, transformation logic, and schema handling you already have, so the data reaching your destination stays consistent with the data already there.

This guide lays out the steps to make that switch without downtime, based on what we’ve learned helping teams move off Fivetran.

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Why Are Teams Moving Away From Fivetran?

1. Pricing Unpredictability of Fivetran

Since Fivetran introduced its MAR-based pricing model in March 2025, estimating the monthly spend based on data volume usage has become more difficult.

Even though Fivetran states that the effective cost per MAR reduces as data volume increases, when we tested this across different MAR volumes, we found that the overall cost continued to increase significantly as data volume increased.

To add to the bill, Fivetran has also introduced a $5 base fee for each connection. Since mid-market and enterprise companies usually run dozens of small connections, the costs quickly add up.

Transformations and activation are also billed separately, which, based on our analysis, can account for more than 70% of the overall cost in some scenarios.

Source

With multiple pricing components involved, companies need to account for MAR usage, connections, transformations, and activation when estimating their monthly Fivetran spend.

2. Support Delays

Fivetran’s support is divided into different levels based on the plan.

The Free plan includes documentation and email support, with response times of up to 48 hours. The Standard plan reduces the response time to between 4 and 24 hours.

Both plans include Fivetran’s Core Service SLA. This assures the availability of the Fivetran platform, but does not guarantee that data from your connectors reaches the destination as intended.

Though Fivetran offers a Data Delivery SLA that guarantees 99.9% data delivery for eligible, properly configured connectors, along with a one-hour support response time, the catch is that both are reserved for its higher-tier plans.

Multiple customer conversations show how difficult it can be to manage pipeline issues on lower support tiers. In some cases, customers have had to build an additional pipeline to keep their data up to date while the original issue remained unresolved.

3. Limited Visibility Into Pipeline Issues

Troubleshooting a pipeline issue can become difficult when you have limited visibility into what is happening across the source, connector, transformations, and destination.

Issues such as schema changes, authentication failures, source API problems, or failed syncs can require teams to investigate different parts of the pipeline to identify the cause.

Source

For companies managing a large number of connectors, this can increase the time required to identify and resolve pipeline issues, especially when combined with difficulty reaching the Fivetran support team.

“Hevo unlocked unmatched reliability and zero downtime for Thoughtspot, cutting infrastructure costs by 85% and ETL tools expenses by 50%. Hevo also empowered analytics users and boosted data usage by 30-35% with its user-friendly interface.”

Ramkumar Natarajan

Senior Manager, Data Operations

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Why is Hevodata the Best Fivetran Alternative?

Two of the major challenges we have seen from companies looking for an alternative to Fivetran are unpredictable pricing and limited support.

Hevo addresses these with fixed pricing for unlimited data volume, agentic monitoring, and 24/7 human support. Support is also available across all paid plans without requiring you to move to a higher tier to access support-related features.

The next challenge is safely migrating your existing Fivetran pipelines to the new ETL platform. As discussed above, Hevo simplifies this through Fivetran-parity connectors, the option to continue from where your Fivetran pipeline was paused, and dedicated migration support.

Here is what you get when moving from Fivetran to Hevo:

• Fixed pricing with unlimited data volume.
• Agentic monitoring that automatically raises 98% of support tickets when pipeline issues are identified, backed by 24/7 human support.
• No support-tier gating across paid plans.
• Fivetran-parity connectors that allow you to continue using your existing schema and transformation logic.
• Dedicated migration support to help with the migration end-to-end.
• The option to run three critical pipelines in parallel for free for the first three months, allowing you to validate the setup before completely moving away from Fivetran.

“It only took us three days to move from Fivetran, which we used for 5-6 months, to Hevo. It was as simple as reconfiguring the settings, and Hevo was all set to show its capabilities in action”

Oleg Lekuchev

VP of Information Technology, ElectroNeek

What Factors Affect Fivetran Migration Effort?

The effort required to migrate away from Fivetran depends on your existing data setup. A company with a few simple pipelines can migrate relatively quickly, while an environment with multiple connectors, transformations, and downstream dependencies will require more planning and testing.

1. Connector Coverage

Start by checking whether the new ETL platform supports all the sources and destinations you currently use with Fivetran.

For example, if you have 20 Fivetran connectors and the new platform supports all 20 natively, you can recreate those pipelines directly. If some connectors are not supported, you may need to use a REST API or build a custom connector, which adds more work to the migration.

The number of connectors also matters. Each connector needs to be configured, tested, and validated before it can replace the corresponding Fivetran pipeline.

2. Volume of Historical Data

The migration effort will depend on whether you plan to reload your historical data or continue from where the existing Fivetran pipeline stops.

A full historical backfill can take significantly more time for companies with large datasets. It can also increase the compute required at the destination, especially when loading large tables into a data warehouse such as Snowflake.

If the historical data already loaded by Fivetran can remain in the destination, the migration becomes simpler. You can pause the Fivetran pipeline at a defined point and configure the new pipeline to resume loading data from that point.

3. Schema and Table Mapping

Check how Fivetran currently creates schemas, tables, columns, and data types in your destination.

Your dashboards, reports, SQL queries, BI tools, and other downstream systems may already depend on this structure. Changing table names, column names, or data types during migration can require changes across these downstream systems.

If the new ETL platform can maintain the same output schema as Fivetran, much of this additional work can be avoided.

You should still verify the schema for each migrated connector. Small differences in data types, timestamps, naming conventions, or the handling of specific fields can affect downstream queries and reports.

4. Pipeline Configuration

Each Fivetran pipeline may have its own configuration that needs to be recreated in the new platform.

This can include sync frequency, selected tables and columns, filters, error handling, alerts, data masking, and other connector-specific settings.

A standard pipeline with minimal configuration will require less work to recreate. Companies with heavily customized pipelines will need to document and replicate these settings before switching.

5. Complexity of Transformations

If you are using Fivetran’s transformation capabilities or its dbt integration, document the existing transformation logic before starting the migration.

Simple pipelines that move data directly from the source to the destination require less migration work. Pipelines with multiple transformations will require additional time to recreate and test that logic in the new environment.

After recreating the transformations, compare the output from both pipelines to confirm that the transformed data reaching the destination remains consistent.

Why Is Migrating from Fivetran to Hevo Easier?

1. Full Connector Coverage from Day One

Hevo provides 150+ pre-built connectors covering the most critical data sources.

If a connector you need is not available, Hevo has a dedicated SWAT team that can build custom connectors. You can also use Connect AI, Hevo’s connector builder agent, to build REST API-based connectors that are ready to use within two hours.

2. Hevo replicates the exact schema of Fivetran

Hevo’s connectors allow you to continue using the same schema that Fivetran was producing in your destination.

Meaning, you can pause your Fivetran pipeline and configure Hevo to start loading data from that point. This allows you to skip reloading the historical data that Fivetran has already moved to your destination, reducing the overall complexity. 

If you want to continue with your existing Fivetran schema and transformation logic, Hevo can maintain the same setup. No schema or table remapping is required, and you do not have to rewrite your existing transformations or dashboards.

This reduces the migration effort associated with historical data, schema mapping, transformations, and downstream dependencies.

3. White-Glove Onboarding With Hevo’s Migration Squad

Hevo provides a dedicated migration squad to support the migration end-to-end.

Our team works with you through the setup and migration process, reducing the amount of pipeline configuration you need to manage on your own.

Move away from Fivetran to Hevo with a guided migration

Hevo's dedicated migration squad handles historical data, schema mapping, and transformations, ensuring nothing breaks when you switch.

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How to Plan a Smooth Migration from Fivetran

Data migration without a plan means downtime, lost data, and broken dashboards. Here’s how you can plan to seamlessly migrate from Fivetran .

1. Audit your current setup

Before you evaluate a new setup, understand the existing one. Start by listing every data source connected through Fivetran, including databases, SaaS apps, and custom integrations. For a quick refresher about this, see What is Fivetran?

Document the downstream dependencies: dashboards, reports, automated workflows, and any applications that use Fivetran’s API for orchestration or monitoring. These may need to be rewritten for the new platform.

2. Set success criteria

Decide what your goals are with this migration. Keep your success criteria as detailed as possible. If your target is cost reduction, include precise dollar amounts and defined timelines for savings. Define measurable data quality goals to maintain stakeholder trust.

3. Choose the right alternative

Decide which data migration tool will replace Fivetran. Analyze your team’s technical skills, budget, and operational needs. Compare the total cost of ownership over several years for data pipeline automation, factoring in licensing, infrastructure, and staffing.

How to Design Your Migration Strategy

1. Phased migration strategy

Migrating everything at once is risky. Instead, start small with low-risk, non-critical connectors and test how the platform handles your data. Once you are confident that things are running smoothly, gradually migrate higher-priority sources.

2. Parallel validation framework

Use both Fivetran and your new tool simultaneously for a period. This process provides a clear comparison of the functions and also gives your employees time to understand and implement the tool.

How to Execute the Migration

A phased rollout is the safest approach. Rushing a full cutover introduces unnecessary risk.

Step 1: Environment setup and testing

• What to do: Stand up development and staging environments that mirror your Fivetran production setup. Run representative data through the new platform, including edge cases, anomalies, and high-volume scenarios.
• Why it matters: This phase surfaces compatibility issues before any production data is at risk. Automate data quality checks that compare source and destination outputs, so validation is consistent and repeatable.
• Key checkpoint: Your staging environment should handle the same data complexity as production before you proceed.

Step 2: Pilot migration

• What to do: Select two or three low-risk, non-critical source connections and migrate them first. Run complete historical data imports, then validate incremental syncs.
• Why it matters: A pilot gives you real-world confidence in the new platform without disrupting core operations. Use row counts, checksums, and business logic checks to confirm accuracy.
• Key checkpoint: Data outputs from the new platform should match Fivetran’s outputs for the same source connections before you expand the scope.

Step 3: Full migration rollout

• What to do: Once the pilot is validated, migrate the remaining connectors in batches, starting with the highest-priority ones. Keep both systems running in parallel throughout to ensure continuity.
• Why it matters: Running systems in parallel means any issue in the new platform can be caught and corrected without impacting downstream consumers. It also gives your team time to get comfortable with the new tooling.

Key checkpoint: Schedule the final cutover when Fivetran is no longer the system of record during a low-traffic maintenance window. Communicate the timeline to stakeholders in advance

Post-Migration Optimization

1. Immediate validation

Run smoke tests across all downstream systems. Check that dashboards load properly and refresh on schedule. Ensure automated reports are still generated and API connections are delivering accurate data without interruptions.

2. Ongoing operations

Track latency, error rates, and data quality to address issues before they cause outages. Keep an eye on resource usage and review performance regularly to understand where you can cut costs without sacrificing speed or reliability.

3. Decommissioning Fivetran

Do not pull the plug on Fivetran immediately. Wait until the new system has run smoothly for at least two to four weeks. Archive your Fivetran configurations and related documentation. Phase out your connectors gradually to provide a safety net.

FAQ about migration from Fivetran

For teams still doing early-stage evaluation, Fivetran FAQs is a useful reference before planning a migration.