Hevo vs Fivetran vs Airbyte: Which ELT Tool Should You Pick in 2026?

Last updated: October 2025

Introduction

Choosing an ELT tool used to be simple: Fivetran was the obvious pick if you had the budget, and you built it yourself if you didn't. That's changed. Hevo has matured into a serious mid-market contender, and Airbyte's open-source model has captured a huge developer community. All three get data from point A to point B. The differences are in pricing, reliability, and what happens when something breaks. We've deployed all three across client projects, so this comparison comes from real implementations, not product pages.

Pricing Models

This is usually the deciding factor, so let's start here.

Fivetran: Monthly Active Rows (MAR)

Fivetran charges based on Monthly Active Rows - the number of unique rows that were updated or inserted in your source tables during the billing period. This sounds straightforward until you realize that a frequently-updated table (like an orders table with status changes) counts the same row multiple times if it's modified multiple times in a month. A 10M-row orders table where 30% of rows get status updates weekly could generate 12M+ MARs per month. The pricing tiers start reasonable but scale steeply above 5M MAR.

Hevo: Event-Based Pricing

Hevo charges per event (essentially per row synced). Their pricing is more predictable than Fivetran's because you pay for what actually moves through the pipeline. A 10M-row initial sync counts as 10M events. A subsequent incremental sync that moves 50K changed rows counts as 50K events. For most mid-market workloads (under 50M events/month), Hevo comes in at roughly 40-60% of what Fivetran would cost for the same data volume.

Airbyte: Open Source + Cloud

Airbyte self-hosted is free. You run it on your own infrastructure (Docker or Kubernetes) and pay only for compute and storage. The catch is operational overhead: you're responsible for upgrades, monitoring, connector updates, and scaling. Airbyte Cloud is their managed offering with pricing comparable to Hevo. For a startup processing under 10M rows/month, self-hosted Airbyte on a $200/month VM is hard to beat on cost.

Connector Coverage

• Fivetran: 500+ connectors. All built and maintained by Fivetran's engineering team. This is Fivetran's strongest advantage. If you need a connector for an obscure SaaS tool, Fivetran probably has it. The connectors are well-tested and handle API changes, rate limits, and pagination automatically.
• Hevo: 150+ connectors. Smaller catalog, but every connector is managed and tested by Hevo. They cover the major sources: databases (MySQL, PostgreSQL, MongoDB, SQL Server), SaaS (Salesforce, HubSpot, Google Ads, Facebook Ads), and cloud storage (S3, GCS). If your source isn't in their catalog, you're out of luck unless you use their REST API connector.
• Airbyte: 350+ connectors. Here's where it gets nuanced. About 100 of these are community-contributed and vary significantly in quality and maintenance. The core connectors (major databases, popular SaaS tools) are solid. Community connectors for niche tools may break when the upstream API changes and take weeks to get fixed. You can also build custom connectors using Airbyte's CDK (Connector Development Kit), which is genuinely useful if you have proprietary sources.

Schema Migration and Data Quality

When your source schema changes - a column is added, renamed, or its type changes - what happens to your pipeline?

• Fivetran handles schema changes automatically. New columns get added to the destination. Column type changes are handled gracefully (widening a VARCHAR, for example). Deleted columns are soft-deleted in the destination. This is genuinely best-in-class and saves hours of maintenance.
• Hevo handles most schema changes well. New columns are propagated. Type changes are handled for common scenarios. It's not as seamless as Fivetran for edge cases (like a column changing from INT to VARCHAR), but it covers 90% of real-world schema changes without intervention.
• Airbyte has improved significantly here but still depends on the connector. Core connectors handle schema changes reasonably. Community connectors may require manual intervention or pipeline reconfiguration when schemas change. For critical production pipelines, this is a real consideration.

CDC (Change Data Capture) Support

CDC is how you replicate database changes incrementally without full table scans. All three support it, but the implementations differ. For context on how CDC fits into broader ETL vs analytics workload management, see our dedicated guide.

• Fivetran: Native log-based CDC for all major databases. It reads the database's binary log (MySQL binlog, PostgreSQL WAL, SQL Server CDC tables) directly. Setup is straightforward, and the replication is reliable. Fivetran handles log position tracking, reconnection after failures, and initial snapshots automatically.
• Hevo: Also supports native log-based CDC for MySQL, PostgreSQL, MongoDB, and SQL Server. The implementation is comparable to Fivetran in reliability. Hevo's CDC dashboard shows replication lag in real time, which is useful for monitoring.
• Airbyte: CDC support varies by connector. The PostgreSQL CDC connector (using Debezium under the hood) is mature and reliable. MySQL CDC is solid. But some database connectors fall back to query-based replication (periodic SELECT with a cursor column), which is less efficient and can miss deletes.

Monitoring and Alerting

When a pipeline breaks at 3am, how fast do you find out and how much context do you get?

• Fivetran: Built-in alerting via email, Slack, PagerDuty, and webhooks. The error messages are clear and usually include the root cause. The dashboard shows sync history, row counts, and schema changes. Fivetran also logs every API call and transformation, which helps with debugging.
• Hevo: Good monitoring dashboard with pipeline health, event volume, and error logs. Supports Slack and email alerts. Hevo's error categorization (source errors vs transformation errors vs destination errors) makes triage faster.
• Airbyte: Self-hosted monitoring requires you to set up your own alerting (most teams use the Airbyte API + a monitoring tool like Grafana). Airbyte Cloud has built-in monitoring comparable to Hevo. The error messages from community connectors can be cryptic.

Transformation Capabilities

• Fivetran: Tight dbt integration. Fivetran can trigger dbt Cloud runs after a sync completes. They also offer Fivetran Transformations (SQL-based) for simple post-load transforms. The dbt integration is production-grade.
• Hevo: Built-in transformation layer with a drag-and-drop interface and Python scripting. You can filter, rename, mask, and transform data before it hits the destination. It's not as powerful as dbt, but it handles 80% of common transform needs without a separate tool.
• Airbyte: Airbyte is extract-and-load only. No built-in transformations. You need dbt or another transformation layer downstream. This is a deliberate design choice - Airbyte focuses on doing EL well and leaves the T to purpose-built tools.

When to Pick Each

Pick Fivetran When:

• Budget isn't the primary constraint and you want the most hands-off experience
• You need connectors for niche SaaS tools that Hevo and Airbyte don't support
• Automatic schema migration is critical (highly dynamic source schemas)
• You're already invested in the dbt ecosystem and want tight integration

Pick Hevo When:

• You're mid-market and need predictable, event-based pricing
• You want a managed service with good Snowflake integration (see our Hevo + Snowflake setup guide)
• You need built-in transformations without adding dbt to your stack
• Your sources are common databases and popular SaaS tools (covered by Hevo's 150+ connectors)

Pick Airbyte When:

• You want to self-host for cost or compliance reasons
• You need custom connectors for proprietary or internal APIs
• You're a startup optimizing for cost and have engineering capacity for ops
• You need community connectors for long-tail SaaS tools not covered by Hevo

Real Gotchas We've Encountered

• Fivetran's pricing can surprise you. A client's Salesforce connector went from $2K/month to $8K/month after a data migration that updated timestamps on 40M historical records. Every updated row counted as an active row. The spike was temporary, but the bill was real.
• Hevo's Salesforce connector doesn't support custom objects by default. You need to request custom object access through their support team. This took 3 business days on one project, which delayed our go-live. Standard objects work out of the box.
• Airbyte's community connectors can break without warning. An upstream API change to a SaaS tool's REST API broke a community connector on a Friday. The fix wasn't merged until Tuesday. If you depend on community connectors for production pipelines, have a fallback plan.
• All three struggle with really high-cardinality schemas. If your source has 500+ columns (we've seen this with clinical data systems), initial syncs can be slow and schema inference can be unreliable. Test with your actual schema before committing.

Key Takeaways

• Fivetran is the premium option: widest connector coverage, best schema handling, highest price. Worth it if your data sources are diverse and you want zero maintenance.
• Hevo is the mid-market sweet spot: good connector coverage, predictable pricing, built-in transforms. Ideal for teams that want managed ELT without enterprise pricing.
• Airbyte is the developer-first option: self-host for free, build custom connectors, but own the ops. Best for engineering-heavy teams that want control.
• All three integrate well with Snowflake. Your choice should be driven by budget, connector needs, and how much operational overhead you're willing to accept.
• Test with your actual data sources before committing. The connector quality for your specific sources matters more than the total connector count.

Frequently Asked Questions