How to Migrate from Fivetran to CData Sync: A Step-by-Step Guide

Fivetran’s ease of use helped you get started with modern data pipelines—but as your business grows, you may be looking for more flexibility, cost control, and deployment options. That’s where CData Sync comes in. With support for 350+ data sources and destinations, predictable pricing, and on-prem or cloud deployment, Sync offers a powerful alternative for teams looking to scale without surprises.

In this post, we’ll walk through how to migrate from Fivetran to Sync in a few straightforward steps—saving you time and ensuring a seamless transition.

Why switch from Fivetran to CData Sync?

Sync offers:

• Deployment flexibility – Install on-premises, in your private cloud (AWS, Azure, GCP), or run as a managed SaaS solution.
• Fixed-cost pricing – No per-row pricing. Sync charges by the number of connections, not usage volume.
• Enterprise-grade security – Keep everything within your firewall or VPC.
• Broad connectivity – Support for legacy systems, flat files, REST/ODATA APIs, and modern SaaS platforms.
• Built-in transformations – Apply in-flight transformations or integrate with dbt without needing a separate service.

Time-saving tip: If you already use dbt in Fivetran, Sync’s dbt support lets you preserve your transformation layer with minimal change.

Technical tips to decode your Fivetran environment before migration

Setting up CData Sync is easier when you fully understand your current Fivetran setup. Here are 5 expert-level tips to accelerate a smooth transition:

1. Export everything via API
   Use Fivetran’s API to extract full connector configurations and schema mappings. Automate it for large environments.

• • Fivetran docs: Retrieve connector configuration metadata
  • Fivetran docs: Retrieve connection details

2. Map transformations up front
   Identify dbt models or in-connector transformations. You can replicate or enhance them in Sync using built-in logic or dbt integration.
3. Know your schema drift behavior
   Check whether new columns/tables are added automatically. Set equivalent expectations in Sync for schema change control.
4. Inventory downstream dependencies
   Track which BI dashboards or apps rely on Fivetran-fed data. It’ll help you test and cut over in a structured, low-risk way.

Time-saving tip: Create a spreadsheet mapping each Fivetran connector to its destination, transformation logic, and downstream usage. It becomes your blueprint for rebuilding jobs in Sync.

Step 1: Audit your existing Fivetran setup

Before migrating, review your active pipelines:

• List all source connectors
• Document destinations and sync schedules
• Capture any transformation logic
• Identify data freshness requirements and downstream dependencies

Time-saving tip: Export connector settings from Fivetran and keep them side-by-side as you configure jobs in Sync.

Step 2: Set up CData Sync

• Download and install CData Sync
• Activate your license or begin a free trial
• Use the UI to set up source and destination Connections

Time-saving tip: Sync’s UI allows test connections, schema previews, and job templates to speed up configuration.

Step 3: Rebuild your data pipelines

For each pipeline you have in Fivetran:

1. Create a Replication Job
   1. Choose the source and destination
   2. Select the tables you want to replicate
2. Apply Transformations (optional)
   1. Use Sync’s built-in tools for masking, filtering, and enrichment
   2. Or plug in dbt for more complex logic
3. Set Up Schedules
   1. Match Fivetran’s sync frequency using flexible scheduling options

Time-saving tip: Sync supports Change Data Capture (CDC) for many sources, enabling incremental syncs and reducing compute overhead.

Step 4: Test and validate

• Run each job manually and review the logs
• Check row counts and data values in your destination systems
• Validate against dashboards, reports, or queries used in production

Time-saving tip: Sync supports dry-run preview and record-count validation to test jobs before pushing large volumes of data.

Step 5: Transition to production

• Plan a cutover time when usage is low
• Update downstream tools to reference the new tables populated by Sync
• Disable Fivetran connectors once Sync is fully live

Step 6: Monitor and optimize

• Use the Job Monitor to track performance and failures
• Adjust schedules or job parameters for optimal throughput
• Archive logs and job history for auditing

Time-saving tip: Sync’s Workspaces feature lets you isolate environments (dev/staging/prod) and export/import configs for repeatable setup.

Migrating at scale? Use Workspaces

If you’re supporting multiple departments or clients:

• Create a Workspace for each environment or tenant
• Export and import Workspaces to quickly replicate configurations
• Isolate access and job schedules by team

Conclusion

Fivetran might’ve helped you get started—but as your data integration needs evolve, Sync gives you full control. With flexible deployment, unlimited sync volume, built-in transformations, and robust connectivity, it’s an ideal Fivetran alternative for growing data teams.

Start your free trial today at cdata.com/sync, or talk to a solution engineer to get help with your migration.

Resources

• Sync product tour
• Documentation
• Compare Sync vs. Fivetran
• Get Started with dbt in Sync