10 Best Fivetran Alternatives: Tested & Reviewed for 2026

While all Fivetran alternatives can move data from disparate sources to a database like Snowflake or BigQuery, the differences lie in their pricing, the integrations and connectors they support, and the quality of support they offer across different customer tiers.

That’s why, besides gauging the ability of the software to extract, load, transform, or transfer data, it becomes imperative to compare these tools on factors that would directly impact your monthly budget, how reliably they run, and how well they fit your current tech stack.

That’s exactly what we did for this article. We tested the top 10 Fivetran alternatives in real-world scenarios with real data workloads to see how pricing varies across use cases, where each tool breaks down, and how quickly its support team gets you a resolution once something goes wrong.

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Quick Comparison: 10 Best Fivetran Alternatives in 2026

Category	Tool	Best For	Pricing Model	Support	Connector / Migration Notes
Managed & No-Code SaaS	Hevo	Teams that want simple, managed pipelines with predictable costs	Pay as you go (event-based) and fixed pricing with unlimited data volume	24/7 human support across paid plans	150+ connectors; Fivetran schema support and parallel migration
Managed & No-Code SaaS	Integrate.io	Flexible ETL and Reverse ETL	Fixed-fee	White-glove support options	ETL, ELT, CDC, Reverse ETL
Managed & No-Code SaaS	Stitch	Small teams with straightforward replication needs	Row-based	Chat and support options	Lightweight setup and common integrations
Managed & No-Code SaaS	Rivery	Teams combining ELT with orchestration	Usage-based credits	Paid support and enterprise options	Strong workflow and activation support
Managed & No-Code SaaS	Skyvia	SMBs needing wizard-based integration	Record-based	Plan-dependent	No-code setup, backup, sync, and REST connectors
Open-Source & Developer-Focused	Airbyte	Engineering teams needing open-source flexibility	Usage/capacity-based or self-hosted	Cloud and community options	Large connector library and custom connector development
Open-Source & Developer-Focused	dlt	Python-first teams building pipelines as code	Open source + platform options	Community/platform dependent	Full code control and schema handling
Open-Source & Developer-Focused	Meltano	Developer-driven DataOps workflows	Open source + paid support	Support depends on deployment	Git-native, Singer-based architecture
Cloud-Native & Warehouse ELT	AWS Glue	Organizations already operating heavily in AWS	DPU/usage-based	AWS support plans	Strong AWS integration; custom connectors available
Cloud-Native & Warehouse ELT	Matillion	Teams focused on warehouse-based transformation	Credit-based	Plan-dependent	Visual development and pushdown transformations

Why Teams Look for a Fivetran Alternative

Fivetran is easy to set up and maintain, but recent G2 reviews highlight specific concerns about pricing, support response times, connector failures, data-quality monitoring, and technical effort.

1. Pricing Becomes Expensive as Usage Grows

Fivetran’s consumption-based pricing can become expensive when data volumes and update rates increase.

For high-volume sources such as Oracle, an ever-growing number of Monthly Active Rows can increase the bill. Teams running many connectors or frequently updated tables may find it difficult to predict their monthly cost before the usage appears on the invoice.

Fivetran claims that the cost reduces as the volume increases, but we have tested this ourselves to find that the claim is false

“Pricing can become a significant concern, especially for high-volume source systems like Oracle, since Fivetran\'s consumption-based model scales quickly.”

Umesh Data Engineer

Read review

2. Support Response Times Can Vary

Fivetran provides 24/7 support, but the initial response time depends on the pricing plan. For a Severity 1 (high-priority) issue, Standard customers can wait up to 4 hours, while Enterprise and Business Critical customers get 1 hour, and Premium customers get 30 minutes.

Waiting four hours for the first response during a critical pipeline failure can create a major impact on production workflows, causing failed downstream jobs, delayed reports, incomplete data, and other business processes to be affected. Also, they did not mention the resolution time in their SLAs.

“Support is helpful, although response times can vary. I\'d also like to see smarter monitoring that flags unusual sync behavior.”

Humphrey Z Staff Analytics Engineer

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3. Connectors Can Break and Leave Data Gaps

Some users report individual connectors failing repeatedly, which can stop new data from reaching the destination.

One recent G2 review describes an Instagram connector breaking every two weeks and leaving blank data for the days when it was unavailable. For teams that rely on that data for reporting or analysis, repeated connector failures can result in missing historical records that require manual recovery.

“There have been cases where connectors have stopped working or not syncing, without any updates on the status page or in incident reports. These are jobs that are critical to our operation, and we received no news about incidents.”

Verified User

Read review

4. Limited Data-Quality Monitoring

A pipeline can complete successfully while the data itself contains unexpected changes, such as a sudden drop in row counts or duplicate records.

A recent G2 review specifically mentions the lack of anomaly detection and duplicate detection, and the need to identify unusual spikes or drops in row counts. Without these checks, teams may discover a data problem only after it affects a report, dashboard, or downstream workflow.

“Our primary use case is data movement and integration, so I would like to see more capabilities that help identify data-quality issues, explain sync problems, detect anomalies, or provide more intelligent recommendations around pipelines.”

Vishal K Data Engineer

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5. Complex Use Cases Can Require More Technical Knowledge

Fivetran is straightforward for common data ingestion, but more complex queries can require SQL and additional technical knowledge.

One G2 reviewer said Fivetran can feel overwhelming and confusing at first, while another specifically mentioned the need for technical knowledge or SQL for complex queries. Teams with limited engineering resources may therefore need more technical involvement as their use cases become more complex.

“For MongoDB, while the ingestion and unnesting capabilities work very well, some advanced configurations and transformation workflows could be made more intuitive and easier to manage directly through the UI.”

Gautam Ashish G Senior Data Analyst

Read review

If any of these apply to your team, the Fivetran alternatives below are worth a close look.

The 10 Best Fivetran Alternatives in 2026

1. Hevo Data – Built for teams that value simplicity, reliability, and predictable pricing

Best for: Mid-market teams that want managed ELT, predictable pricing, strong support, and less pipeline maintenance.

4.4/5 on G2 (293 reviews)

Hevo is a modern, reliable data pipeline platform that helps data teams move data from a variety of sources to major cloud warehouses with simplicity, transparency, and reliability.

Hevo is ideal for teams that want to spend less time managing pipeline infrastructure, because with Hevo, instead of building connectors, manually monitoring every sync, and handling failures themselves, teams can use Hevo’s managed pipelines, built-in monitoring, and automated recovery features.

Key Features

• No-code pipelines – Create and manage data pipelines through a visual interface without writing or maintaining pipeline code.
• 150+ business-critical connectors – Connect the core SaaS applications, databases, files, and other business systems your team relies on, with the focus on connector quality and real-world coverage rather than just the number.
• Pipeline monitoring: See pipeline activity, errors, and record-level issues via dashboards, logs, and smart alerts.
• Schema handling – Detect schema changes and update mappings without having to rebuild affected pipelines manually.
• CDC support – Captures inserts, updates, and deletes from supported databases so changes continue to flow to your destination.
• dbt integration – Move ingested data into your downstream dbt workflows without adding another step between ingestion and transformation.

Pros

• 24/7 dedicated human support: Every customer gets support across multiple channels, including email and Slack.
• Dedicated account manager: Customers have a dedicated contact who can help with Hevo setup, usage, and issues.
• Proactive issue handling: Hevo automatically raises tickets when a pipeline breaks and resolves 98% of issues before they become a customer problem.
• Record-level visibility: Smart alerts and record-level isolation show what broke and when without requiring teams to dig through logs.
• Support isn’t tier-gated: These support capabilities are included across every paid plan.

Cons

• Cloud-based only
• Smaller connector catalog than Fivetran’s 700+ connectors
• Business Critical pricing is custom for higher-volume workloads

Why Choose Hevo Over Fivetran

• Lower engineering effort: Hevo manages pipeline infrastructure, monitoring, failure recovery, and schema handling, rather than pushing more operational work onto the data team.
• Better support access: Every paid Hevo customer gets dedicated human support across multiple channels, along with a dedicated account manager.
• More direct pipeline visibility: Smart alerts and record-level isolation help teams find the specific problem without manually digging through multiple systems.
• More practical connector coverage: Hevo has 150+ connectors covering around 90% of common business use cases. When a required connector is missing, its connector SWAT team can build one in 2 to 4 weeks. Custom REST API connectors can also be built with Connect AI in under 2 hours.
• Less migration disruption: Teams can continue using their existing Fivetran schema, so downstream dashboards and models don’t need to be rebuilt. You can also run up to three pipelines in parallel at no extra cost while validating the migration. Most teams complete the move within 14 days.

Customer Review

We did a proper evaluation between Hevo and its competitors. We realized that Hevo provided the best value out of all of them; it had all the features that we wanted at a price that we were comfortable with. It was the best option for us.

Prudhvi Vasa

Head of Data

View Customer Story

Pricing

• Free – For smaller teams testing data pipelines.
• Starter Plan – Starting at $265 per month – For growing teams with regular workloads.
• Professional Plan – $750 per month – For higher-volume production data pipelines.
• Business Critical – For more than 100M monthly events – Custom pricing for larger enterprise workloads. Contact the Hevo sales team.

See the Hevo pricing page for the latest plan limits, included features, and pricing details.

Looking for a Fivetran Alternative?

Hevo prices on the events you move, with no MAR spikes or credit math, so your costs stay low even as volumes climb.

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2. Integrate.io – Best for Flexible ETL and Reverse ETL

Best for: Teams that need ETL, ELT, CDC, Reverse ETL, and API workflows on a single platform.

Integrate.io is a cloud data integration platform that combines ETL, ELT, CDC, Reverse ETL, and API workflows through a visual interface for teams managing business data.

Key Features

• ETL and ELT workflows – Build both pre-load and post-load data pipelines from one platform.
• Visual pipeline builder – Use drag-and-drop components, SQL, and configurable dataflow steps.
• Reverse ETL – Send processed warehouse data back into SaaS and operational systems.

Pros

• Has a visual pipeline builder with SQL and drag-and-drop options.
• Contains prebuilt connectors for various tools.
• It supports API integrations and custom dataflows with SQL or scripts.

Cons

• Limited documentation: Some users may need extra guidance because the available documentation does not cover everything in detail.
• Manual setup: Performance tuning and job scheduling may need some manual work.
• Usage-based pricing: Costs can be harder to predict as usage increases or add-ons are added.

“The API documentation could be more detailed, especially in the CURL examples and in handling JSON data using functions like map and bag to iterate over objects.”

Praful P Data Engineer

Read review

Why Teams Choose Integrate.io as a Fivetran Alternative

• More pipeline options: Integrate.io supports ETL, ELT, CDC, and Reverse ETL, enabling teams to use it for more than just managed data ingestion.
• More transformation control: Teams can use visual components, SQL, and custom workflows when Fivetran’s managed approach feels restrictive.
• Fixed-fee option: Teams that want to move away from MAR-based billing can evaluate Integrate.io’s fixed-fee pricing.

Pricing

Plans typically start at around $1,999/month.

Enterprise plans are custom-quoted based on security, compliance, and workload requirements.

3. Stitch – Best for basic data replication

Best for: Small teams that need straightforward, managed replication without a large operational setup.

Stitch is a managed data loader for smaller teams. It moves the data from common sources into cloud data warehouses without requiring teams to manage complex pipeline infrastructure or write custom code.

Key Features

• Managed data loading – Move the data from supported sources into cloud data warehouses.
• Configurable replication – Set how often each integration should sync data.
• Simple setup – Connect a source and choose the data you want to load into the warehouse.

Pros

• You can set up quickly, and it’s easy to learn
• Simple interface that non-engineering users can work with
• Works well for smaller datasets and less frequent data syncs

Cons

• Fewer connectors than many modern ELT platforms
• Support can be slow when issues come up
• Data syncs may not be fast enough for use cases that need up-to-date data

“Customer Support is not very active. No new connectors have been added lately, and maintenance of old connectors has also stopped. Backfilling is a bit difficult”

Pranjal J Technical Lead

Read review

Why Teams Choose Stitch as a Fivetran Alternative

• Simple data replication: Stitch focuses on moving data from sources to the warehouse, which works well for teams that do not need advanced ELT features.
• Simple pricing: Pricing is based on data volume, making costs easier to understand for smaller workloads.
• Less setup: Teams with basic sources and destinations may not need the additional workflow options found in larger platforms.

Pricing

• Standard tiers: Start at around $100 per month, based on row limits.
• Advanced plans: Custom pricing is available for higher data volumes and additional features.

For a side-by-side comparison of pricing, features, and flexibility, see our Fivetran vs Stitch Key Comparisons.

4. Rivery – Best for reverse ETL

Best for: Teams that want managed ELT, workflow orchestration, and reverse ETL.

Rivery is a managed data integration and orchestration platform that combines ELT, workflow automation, and data activation for teams running complex multi-step data pipelines efficiently today.

Key Features

• Workflow orchestration: Build scheduled workflows that connect data ingestion, transformations, and other tasks.
• Reverse ETL: Send data from the warehouse to business and operational tools.
• Transformation options: It uses SQL, Python, or REST APIs to work with data inside your workflows.

Pros

• Combines ELT, orchestration, and reverse ETL in one platform.
• Includes prebuilt connectors for data warehouses and SaaS applications.
• Gives engineering teams different ways to transform data using SQL, Python, or REST APIs.

Cons

• Costs can be difficult to predict because pricing depends on compute and API usage.
• The nested workflow structure, called “Rivers,” can take time for non-technical users to learn.
• Some documentation gaps and unclear error messages can make troubleshooting difficult.
• Users may also run into bugs or ETL issues that affect the overall experience.

Why Teams Choose Rivery as a Fivetran Alternative

• More workflow control: Rivery combines data ingestion and workflow management, reducing the need for separate tools.
• Reverse ETL included: Teams can send warehouse data to business tools without using another platform.
• Flexible transformations: SQL, Python, and REST APIs give engineering teams more control over how data is processed.

Pricing

• Base Plan – Starts at $0.75 per BDU credit with pay-as-you-go pricing.
• Professional Plan – Includes features for smaller data teams.
• Enterprise Plan – Custom pricing with advanced governance, SLAs, and dedicated support.

For an in-depth look at how the two compare across automation and orchestration capabilities, check out our Fivetran vs Rivery Comparison.

5. Skyvia – Best for SMBs needing easy, wizard-based integration

Best for: SMB teams that need no-code data integration, synchronization, and backup without having to build complex pipelines.

Skyvia is a cloud-based data integration platform for teams that work with data across different business applications. It provides no-code ETL, data synchronization, backup, and automation for simpler workflows.

Key Features

• No-code integration – Build workflows through a visual interface without writing pipeline code.
• Flexible scheduling – Set integrations to run on a schedule, from daily runs to more frequent schedules on paid plans.
• Custom connectivity – Connect less-common sources via REST connectors, webhooks, and API access.

Pros

• Easy-to-use interface with a step-by-step workflow builder
• Prebuilt connectors for common SaaS and CRM applications
• Lower starting price than many SaaS ELT platforms

Cons

• Basic transformation options compared with more advanced ELT tools
• Limited in-app notifications and error logs can make troubleshooting harder
• Large datasets or complex workflows may cause jobs to fail

“Sometimes, when a sync has an issue, the alert emails are a bit basic, so you have to log in to see the full story of what went wrong.”

David O Analytics Engineer

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Why Teams Choose Skyvia as a Fivetran Alternative

• Lower starting cost – Skyvia can work well for smaller workloads, where Fivetran may be more than the team needs.
• Backup and sync – Data integration, backup, and synchronization are available on a single platform.
• No-code setup: Teams can build simple workflows with minimal engineering work.

Pricing

• Free Plan – This includes basic integration for smaller data volumes.
• Basic to Professional Plans – Pricing varies based on data volume and connectors.
• Enterprise Plan – Custom pricing is available for high-volume and compliance-focused use cases.

6. Airbyte – Best for open-source, flexible data pipelines

Best for: Engineering teams that want open-source flexibility, self-hosting, and the option to build custom connectors.

Airbyte is an open-source data integration platform offering cloud and self-hosted deployments, extensive connectors, and support for custom connector development for engineering teams that need greater pipeline control.

Key Features

• Open-source deployment: Run Airbyte on your own infrastructure when self-hosting is required.
• Large connector library: Connect a broad range of SaaS applications, databases, and other sources.
• Custom connectors: Use development tools such as the Python CDK to build or modify connectors.

Pros

• Open-source and self-hosted.
• Python-based CDK to create or modify connectors.
• Supports both batch and log-based CDC for databases.

Cons

• Insufficient support leaves users waiting for community responses to fix pipeline issues.
• Requires high maintenance load, including hosting, patching, and version upgrades.
• With many community-created connectors, quality and stability can be inconsistent across sources.

“Some connectors also have occasional syncing issues or rate-limit errors with third-party APIs, which sometimes need manual troubleshooting.”

Verified User

Read review

For a detailed breakdown of how the two platforms compare, explore our Fivetran vs Airbyte: Comprehensive Comparison.

Why Teams Choose Airbyte as a Fivetran Alternative

• Open-source control: Teams can inspect, modify, and manage connectors rather than relying entirely on a vendor-managed connector.
• Self-hosting: Airbyte works for teams that need their own infrastructure for deployment or data residency reasons.
• Connector flexibility: Engineering teams can build connectors when an existing integration does not meet their requirements.

Pricing

• Open-Source Edition – It’s free to use and self-host, with community support.
• Cloud Starter Plan – This starts at $10 per month and includes 4 credits.
• Usage-Based Credits – Extra usage is charged based on data volume and sync frequency.
• Enterprise Edition – Pro and Enterprise plans are priced based on the data processing capacity you need.

A data bill you can plan around

Hevo’s plans start at $265/month with no credits or MAR math to forecast.

Start for free

7. dlt (data load tool) – Best for engineering-led teams that want code-first pipelines

Best for: Python-first data teams that want to write and control their pipelines as code.

dlt is an open-source Python library for building data pipelines that extract data from APIs, databases, or files and load it into warehouses or modern lakes.

Key Features

• Python-based pipelines – Build and manage data pipelines directly in Python instead of using a visual pipeline builder.
• Automatic schema handling – dlt can detect the structure of incoming data and update the schema when the source changes.
• Open-source deployment – Run dlt on your own infrastructure without paying for a platform license.

Pros

• Supports incremental loading and CDC-style workflows, with integrations for dbt and Airflow. dltHub also provides AI-assisted tools for building pipelines.
• The dlt library is free and open source under the MIT license.
• Since the pipelines are written in Python, developers have full control over how they work.

Cons

• You are responsible for the infrastructure, monitoring, maintenance, and uptime. The software is free, but running it still costs money.
• Dlt is a library rather than a managed service. Your team needs to build, deploy, and maintain the pipelines.
• You need Python and engineering skills to use it, so it is not a good option for teams looking for a no-code tool.

Why Teams Choose dlt as a Fivetran Alternative

• More control over pipelines: Developers can access and modify pipeline code directly.
• No MAR-based billing – dlt does not charge based on the number of rows changed. You still need to account for infrastructure and engineering costs.
• Works with existing development tools – Teams can use Python, Git, dbt, and orchestration tools as part of the same workflow.

Pricing

• dltHub platform – Paid plans are available for the managed and AI-assisted platform.
• Open-source dlt library – Free under the MIT license. You pay for the infrastructure needed to run it.

8. Meltano – Best for developer-driven pipelines

Best for: Engineering teams that prefer Git-based, code-first data workflows and direct control over infrastructure.

Meltano is an open-source data integration platform for teams that prefer to manage their pipelines through code. It uses Singer taps and targets for connecting sources and destinations. Teams can also manage pipeline changes through Git and their existing development workflows.

Key Features

• Git-based workflows: They store pipeline settings and configuration alongside the rest of your code.
• Singer ecosystem – Use Singer taps and targets to connect different sources and destinations.
• Local development – Build and test pipelines locally before moving them to production.

Pros

• It is open-source and flexible, giving engineering teams more control
• Works with Git and CI/CD workflows
• Supports custom connectors and local development

Cons

• Requires more engineering work to set up and maintain
• Does not provide a fully managed cloud experience for teams that want minimal maintenance
• Your team needs to manage monitoring, recovery, and pipeline health

Why Teams Choose Meltano as a Fivetran Alternative

• More control over the code – Developers can directly manage how pipelines are configured and run.
• Open-source flexibility – Teams can change and customize the setup instead of relying entirely on a managed vendor.
• Git-based development – Pipeline changes can follow the same review and CI/CD process as other engineering work.

Pricing

• Open Source – Free to self-host and use.
• Team Support – Paid plans are available for support, SLAs, and expert help.
• Managed – Hosted plans are available for teams that want a production environment with enterprise features.

9. AWS Glue – Best for the AWS ecosystem

Best for: Organizations already using AWS services and comfortable managing Spark-based ETL workflows.

AWS Glue is a serverless AWS data integration service for building ETL jobs that connect data stores, transform datasets, and prepare data for analytics workloads efficiently.

Key Features

• AWS integration: Connect Glue jobs with services such as S3, Redshift, Athena, and other AWS components.
• Serverless ETL: Run data processing jobs without provisioning ETL infrastructure.
• Custom connectors: Add connectors for data stores that aren’t supported out of the box.

Pros

• Works well with other AWS services.
• Uses a serverless setup and can scale based on the workload.
• Supports both batch jobs and event-driven workflows.

Cons

• The setup can be difficult for non-technical users.
• Teams need to understand Spark, Python, and AWS IAM to get the most from it.
• There are fewer ready-made connectors for non-AWS SaaS applications.
• Finding and fixing performance issues can take time.

“One challenge with AWS Glue is the learning curve, especially for beginners who are new to Spark or AWS services.”

Alankrita P Software Engineer

Read review

Why Teams Choose AWS Glue as a Fivetran Alternative

• AWS integration – Glue works well when services such as S3, Redshift, Athena, and IAM are already part of the data stack.
• More control: Teams can configure jobs, workers, connections, and custom connectors to meet their needs.
• Custom processing: Glue is useful for ETL jobs that require Spark-based transformations or other AWS-specific processing.

Pricing

• Pay-as-You-Go – You pay based on the DPUs used by your jobs.
• Additional charges: Services such as DataBrew, Data Quality, development endpoints, and Data Catalog storage can increase the total cost.

For a detailed feature-by-feature comparison between the two, explore our Fivetran vs AWS Glue ETL Comparison.

10. Matillion – Best for In-Warehouse Data Transformations

Best for: Teams that want visual pipeline design with transformations pushed into their cloud data warehouse.

Matillion is a cloud-based data platform for building data pipelines, running transformations, and managing workflows. It uses a visual interface and works with modern cloud data warehouses.

Key Features

• Visual pipeline builder – Build data workflows through a visual interface.
• Pushdown transformations – Run transformations directly in supported cloud data warehouses.
• Warehouse integrations – Connect with platforms such as Snowflake, Redshift, BigQuery, and Databricks.

Pros

• Visual tools make it easier to build complex ELT workflows.
• Transformations can run directly in the data warehouse.
• Supports major warehouses such as Snowflake, Redshift, BigQuery, and Databricks.

Cons

• Teams had to set up and manage the platform within their data warehouse environment.
• Transformation jobs use warehouse compute, which can increase costs as usage grows.
• Limited GitHub integration and API options may make development workflows less flexible.

“Maia (the AI part) could be expanded to be really powerful by using information already within the platform, such as execution times, to enable real-world pipeline optimization by reducing run times, which ultimately drives cost.”

Anthony S Lead Data Engineer

Read review

Why Teams Choose Matillion as a Fivetran Alternative

• More focus on transformations: Matillion gives teams greater control when data transformation is a major part of the workflow.
• Visual workflow design – Teams can build complex data workflows through the visual interface instead of writing every step manually.
• Warehouse-native execution: Transformations use the warehouse’s compute instead of relying on an external transformation layer.

For a deeper look at how the two solutions differ in design, flexibility, and performance, explore our Fivetran vs Matillion Key Differences.

Pricing

Matillion uses a credit-based pricing model tied to compute usage and plan tier. All the plans follow a pay-as-you-go model where you are billed on actual usage. The basic plan costs $2 per credit.

• Credit-Based Model: Usage billed in credits; 1 credit = 1 vCore-hour (ETL).

• Editions & Plans: Developer, Teams, and Scale editions.

How to Choose the Right Fivetran Alternative for Your Business

Choosing an alternative becomes easier when you start with the problem that made you look for one. Don’t compare tools on connector count alone. Compare them against the workloads, costs, support needs, and migration effort your team will actually face.

1. Support Quality: How Quickly Can You Get Help When a Pipeline Breaks?

Support becomes important when a production pipeline fails, and your team cannot fix it on its own.

Fivetran’s response time depends on the plan you choose. Check the response time included in the plan you would actually buy. Also, look at what the support team does beyond that response time.

Ask:

• Is support available through email, chat, Slack, or phone?
• Will you have a dedicated support contact?
• Will the support team help to find the cause of the problem?
• Is support included in the plan, or does it cost extra?

Try sending a support request during the evaluation. The response can give you a better idea of the quality of support than a badge on a pricing page.

2. Predictable Pricing: What Happens to Your Bill When Data Changes?

Do not compare tools based only on their starting price. Your actual cost depends on how you use the platform.

Before choosing a tool, estimate:

• Number of connectors
• Records or Events you will move
• Sync frequency
• Historical data loads
• CDC volume
• Number of Destinations
• Expected data growth

Also, check what happens if your data volume doubles.

This is important with Fivetran because MAR is based on data changes. A connector may look affordable at first, but the cost can increase when the data changes more often.

3. Connector Coverage: Does the Tool Support Your Business Sources?

A tool may have hundreds of connectors and still not support an important source your team uses. Start by making a list of the sources you actually need.

For each source, check:

• Is the needed connector available?
• Does it support the tables or objects you need?
• Does it support incremental loading or CDC?
• Can you choose which fields to sync?
• How does it handle the source schema changes?
• Is the connector managed by the vendor or the community?

Fivetran has more than 700 connectors, but the total number is less important than whether it supports the sources your business needs.

4. Data Freshness and Latency: How Quickly Does the Data Need to Update?

A daily reporting pipeline does not need the same update speed as a customer-facing application. Start by deciding how fresh each pipeline needs to be.

Then check whether the platform supports:

• Hourly loads
• 15-minute syncs
• Near-real-time pipelines
• Streaming CDC
• High-volume processing

There is no need to pay for real-time processing if your reports only update once a day. On the other hand, a batch-focused tool may not work if your application needs fresh data every few minutes.

5. Ease of Use and Maintenance: Who Will Manage the Pipelines?

A powerful tool can still create a lot of work for your team.

Check how easy it is to:

• Build a connector
• Handle a schema change
• Retry a failed sync
• Find a bad record
• Set up alerts
• Manage credentials
• Upgrade the platform

Then compare the required work with your team’s skills and size.

A small data team may prefer a managed no-code platform. Teams with strong Python skills may prefer Airbyte, dlt, or Meltano because they offer more control over the pipeline code.

6. Scalability and Deployment: What Happens as Your Data Stack Grows?

Do not look only at whether a tool can handle your current data volume. Think about what you will need as the data stack gets larger.

Check what happens when you add:

• More connectors
• More destinations
• More users
• Higher sync frequency
• Larger CDC workloads
• More regions
• New security requirements

Also, check how the platform can be deployed. If you need self-hosting or close integration with a specific cloud provider, Airbyte or AWS Glue may be better options than a fully managed SaaS platform.

How to Migrate from Fivetran to Hevo

You do not need to move everything at once while leaving Fivetran. You can start by reviewing your current setup, testing the new platform, running both tools together, and switching over only after the data matches.

Phase 1: Audit Your Current Fivetran Setup

The goal is to know exactly what you are moving, so nothing gets left behind.

• Work with our Migration Squad to take inventory of all your connectors, pipeline configurations, transformations, and downstream tools.
• Once that is done, map each Fivetran connector to a Hevo equivalent. If there are any gaps, request that the SWAT team build a custom connector or use Connect AI, our connector builder agent.
• Define the success criteria with the Migration Squad before moving anything.

Phase 2: Run a Pilot Migration (Week One)

The goal is to prove that the migration works with zero risk before going all in.

• Sign up for your Hevo account and connect your destinations.
• Configure your first batch of high-volume connectors with the Migration Squad’s help.
• Validate the data quality and generate a parity report to confirm that Hevo replicates the exact Fivetran schema and table names.

Phase 3: Run Both Platforms in Parallel (Week Two)

The goal is to demonstrate stability before decommissioning Fivetran and fully migrating to Hevo.

• Run both systems side by side and monitor data drift.
• Our Migration Squad will track sync performance and schema changes to ensure everything is working properly.
• Validate the pipelines and get stakeholder sign-off.

Phase 4: Full Migration and Cutover (After Week Two)

After running both platforms in parallel and obtaining stakeholder sign-off, the goal is to migrate all remaining connectors and fully retire Fivetran.

• Our Migration Squad will help you configure the remaining connectors in batches.
• Schedule the cutover during a low-traffic window.
• Run a final sync in both systems and decommission the Fivetran connectors.

For a detailed walkthrough, see our step-by-step Fivetran migration guide.

Why Hevo is the Best Fivetran Alternative

For teams considering moving away from Fivetran due to pricing, support, connector availability, or migration effort, Hevo offers a managed alternative with less pipeline maintenance.

Factor	Fivetran	Hevo
Pricing	MAR-based pricing tied to monthly active rows and connection usage	Pay as you go (event-based) and fixed pricing with unlimited data volume
Support	24/7 global support, with response times based on plan and issue severity	24/7 human support on paid plans through email and Slack
Account support	Additional support resources are available on higher-tier plans	Dedicated account manager for every customer
Pipeline failures	Issues are handled through the support process based on the plan’s response terms	Failed pipelines can automatically raise support tickets, with proactive help for many issues
Pipeline monitoring	Shows the connector status and usage	Provides alerts, logs, record-level isolation, and pipeline status
Connectors	700+ managed connectors	150+ connectors covering around 90% of common business use cases
Missing connectors	Depends on the connectors available in Fivetran’s catalog	The Connector SWAT team can build missing connectors in 2–4 weeks. Custom REST APIs can also be built with Connect AI
Migration	Migration may require changes to schemas and downstream systems	Existing Fivetran schemas can be retained to reduce downstream changes
Parallel migration	Requires separate planning and environments	Up to three pipelines can run in parallel at no extra cost during validation
Typical migration time	Depends on the number of connectors and migration complexity	Most teams can complete the migration within 14 days
Pipeline management	Fivetran manages the pipelines, but some issues may need further investigation	Managed pipelines include monitoring, alerts, retries, and auto-healing

For teams primarily concerned with pricing, support, connector coverage, or migration effort, Hevo offers a simpler way to manage these areas without adding to pipeline maintenance.ing pipelines. With fault-tolerant performance, automated scaling, and complete end-to-end visibility, Hevo gives you a stable ELT foundation without surprise costs or slow vendor support.

Migrate away from Fivetran without breaking a thing

Keep your existing schema, validate the migration in parallel, and move your pipelines to Hevo, a managed platform built for simpler data operations.

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