Fivetran Review: Pricing, Features & What the Data Shows
Automated data pipelines that move data from apps to warehouses without engineering overhead.
What Fivetran Does
Fivetran is the leading automated data pipeline platform, handling the extract-and-load (EL) layer of the modern data stack. It connects to 300+ data sources — SaaS applications, databases, file systems, event streams — and keeps your data warehouse synchronized without engineering maintenance. Founded in 2012, the company has become the default choice for data teams that want reliable pipelines without the overhead of building and maintaining custom ETL scripts. For RevOps teams specifically, Fivetran is the tool that gets your Salesforce, HubSpot, Marketo, and other GTM data into Snowflake or BigQuery for unified analytics.
Fivetran's core value proposition is zero-maintenance pipelines. When Salesforce changes its API, Fivetran handles the update. When HubSpot adds a new object type, Fivetran detects the schema change and adjusts automatically. When your data volume spikes during a product launch, Fivetran scales without intervention. This reliability is what separates Fivetran from DIY approaches — custom ETL scripts break constantly, and maintaining them is a full-time job at any meaningful scale. Fivetran turns data pipeline management from an engineering burden into a managed service.
The platform competes primarily with Airbyte, the open-source alternative that offers similar connectors at lower cost. The trade-off is clear: Fivetran costs more but requires less engineering time to operate. Airbyte costs less but requires data engineering resources to deploy, monitor, and maintain. For companies with dedicated data engineering teams and cost sensitivity, Airbyte is a viable choice. For data teams that want to focus on analysis rather than pipeline maintenance, Fivetran's managed approach typically wins.
The practical buyer consideration is cost at scale. Fivetran's pricing is based on Monthly Active Rows (MAR) — the number of rows that change each month — which means costs scale with data volume rather than connector count. A typical mid-market deployment syncing 5-10 SaaS sources runs $500-3,000/month. But high-volume transactional databases or event-heavy sources can push costs to $10K+/month. Understanding your data volume before signing is critical to avoiding pricing surprises.
Fivetran Key Features
300+ Pre-Built Connectors
Connectors for virtually every SaaS application, database, and file format that a data team encounters. GTM-relevant connectors include Salesforce, HubSpot, Marketo, Google Analytics, LinkedIn Ads, Stripe, and Zendesk. Each connector handles authentication, incremental syncing, schema detection, and error recovery automatically. Most connectors are set up in under 15 minutes — authorize the source, choose a destination, and Fivetran starts syncing. Premium connectors (SAP, Oracle DB) cost more per MAR.
Automatic Schema Detection
When source applications add new fields, tables, or objects, Fivetran detects the schema changes and updates the destination warehouse automatically. This eliminates the most common source of ETL pipeline failures — schema drift breaking custom scripts. For RevOps teams, this means Salesforce custom fields and HubSpot property changes propagate to your warehouse without manual intervention. Schema change notifications alert data teams to review new fields.
Incremental Syncing
Only syncs data that has changed since the last run, reducing data volume, warehouse compute costs, and sync times. Full table resyncs are available when needed. Sync frequency varies by plan: standard connectors support 5-minute to 24-hour intervals, with 1-minute sync available on higher tiers. For real-time analytics needs, the 5-minute sync frequency is adequate for most operational reporting use cases.
Transformations
Built-in dbt integration for running data transformations after loading. Fivetran can trigger dbt models automatically when new data arrives, creating a fully automated ELT pipeline: extract from sources → load to warehouse → transform with dbt. This integration is a significant workflow improvement — it eliminates the need for separate orchestration tools (like Airflow or Dagster) for basic transformation workflows. For complex transformation pipelines, a dedicated orchestrator may still be needed.
Data Observability
Monitors pipeline health, data freshness, and volume anomalies. Alerts fire when syncs fail, when data volumes change unexpectedly (which could indicate a source issue), or when schema changes occur. The observability features help data teams maintain trust in their pipelines — catching a failed Salesforce sync within minutes versus discovering it a week later when a dashboard shows stale data. Log-level debugging is available for troubleshooting sync issues.
Multi-Destination Support
Supports Snowflake, BigQuery, Redshift, Databricks, Azure Synapse, and other major warehouses and lakehouses. You can sync the same sources to multiple destinations — useful for organizations with separate analytics and ML environments. Destination configuration handles warehouse-specific optimizations (clustering keys, partitioning) automatically. Most customers use Snowflake or BigQuery as their primary destination.
Who Uses Fivetran
RevOps Data Centralization
The most relevant Fivetran use case for this audience. RevOps teams sync Salesforce, HubSpot, Marketo, and other GTM tools to a central data warehouse (typically Snowflake or BigQuery) for unified pipeline analytics, marketing attribution, and revenue reporting. Without Fivetran, this data lives in silos — Salesforce reports show pipeline but not marketing touchpoints, HubSpot shows campaign metrics but not closed revenue. Fivetran connects these sources so a BI tool like Looker or Tableau can show the complete picture. A typical mid-market RevOps deployment costs $500-2,000/month for 5-10 SaaS source connections.
Data Team Infrastructure
Data engineering and analytics teams use Fivetran as the ingestion layer of their modern data stack. The typical architecture: Fivetran extracts data from all sources → loads to Snowflake → dbt transforms the raw data into analytics-ready models → Looker or Tableau visualizes the results. Fivetran handles the least glamorous but most failure-prone part of this stack — keeping source data flowing reliably into the warehouse. Teams that previously spent 30-50% of data engineering time maintaining custom pipelines reclaim that capacity for analysis and modeling work.
Product Analytics Pipeline
Product and growth teams sync product usage data (from Segment, Amplitude, or application databases) alongside GTM data to build unified customer analytics. The combined dataset enables product-led growth analysis: which features correlate with conversion, which usage patterns predict churn, and how does product engagement influence sales outcomes. Fivetran handles the high-volume event data from product analytics sources, though costs can escalate quickly with event-heavy sources that generate millions of MAR.
Fivetran Pricing
Free
Up to 500K monthly active rows, limited connectors
Starter
Pay-as-you-go, standard connectors
Standard
All connectors, transformations, multiple destinations
Enterprise
Private networking, SOC 2 Type II, SLAs
Fivetran's pricing is based on Monthly Active Rows (MAR) — the number of distinct rows that are updated, inserted, or deleted in your source data each month. This usage-based model means costs scale with data change volume, not the number of connectors.
The Free tier includes up to 500K MAR with limited connectors — useful for small teams evaluating the platform. The Starter tier uses a credit system at roughly $1/credit with standard connectors. Standard and Enterprise tiers have custom pricing that typically works out to $0.50-$2.00 per thousand MAR, depending on volume commitments and connector types.
For a typical mid-market B2B company syncing Salesforce (100K records), HubSpot (200K contacts), Marketo, Google Analytics, and 2-3 other sources to Snowflake, expect monthly costs of $500-2,000. Enterprise deployments syncing high-volume transactional databases, event streams, or numerous sources can reach $5K-15K/month.
The pricing dynamic to watch is source volatility. A Salesforce connector with 100K records that change slowly might generate 20K MAR. A marketing events table that logs every email send could generate 500K MAR. Sources with high event volumes or frequent record updates drive disproportionate costs. Understanding your source data change patterns is essential before committing to a pricing tier.
Compared to Airbyte: Airbyte's open-source version has no licensing cost but requires data engineering resources to deploy and maintain ($100K+ in equivalent labor for a small team). Airbyte Cloud offers managed hosting at roughly 40-60% of Fivetran's cost per connector, with fewer total connectors available.
Job Market Demand for Fivetran
Fivetran appears in 11 job postings across 8 companies in our database of 23,338+ analyzed job postings. The average salary range for roles requiring Fivetran: $156K - $211K.
Department
- GTM Finance Manager
- Director of Data Engineering
- VP, Data Engineering Technical Lead
- fivetran (3)
- radiant (1)
- point digital finance (1)
- petfolk (1)
- magnit global (1)
Commonly Used With Fivetran
Based on job posting co-occurrence data, these tools are most frequently mentioned alongside Fivetran:
Pros & Cons
Pros
- 300+ pre-built connectors with automatic schema detection
- Zero-maintenance: handles API changes and schema drift automatically
- Fast setup: most connectors running in under 15 minutes
- Supports all major warehouses (Snowflake, BigQuery, Redshift, Databricks)
- Strong data reliability and observability features
Cons
- Usage-based pricing can spike with high-volume data sources
- Less control than custom-built pipelines or open-source alternatives
- Some connectors have sync frequency limitations on lower tiers
- Vendor lock-in: migrating away requires rebuilding pipeline configs
- Premium connectors (SAP, Oracle) cost significantly more
Best for: Data and RevOps teams that need reliable, automated data pipelines without dedicated data engineering resources
Not ideal for: Teams with heavy custom transformation needs during extraction, or companies where $500+/month for data pipelines isn't justified by analytics use cases
Fivetran Alternatives
| Tool | Starting Price | Job Mentions | Best For |
|---|---|---|---|
| Airbyte | $0 | 2 | Data engineering teams that want control over their integration infrastructure without vendor lock-in. Ideal for startups and mid-market companies with some engineering capacity, especially those running modern data stacks with dbt and a cloud warehouse. |
| MuleSoft | ~$50K/year | 10 | Large enterprises with complex integration needs across Salesforce, ERP, and legacy systems |
| Workato | Custom | 5 | Mid-market to enterprise companies that need automation capabilities beyond Zapier but don't want the complexity of MuleSoft |
| Hightouch | $0 | 3 | Data teams with a modern data stack who want to activate warehouse data and potentially replace a traditional CDP |
| Zapier | $0 | 17 | SMBs and ops teams needing quick integrations between SaaS tools without engineering help |
Frequently Asked Questions
How much does Fivetran cost per month?
It depends on data volume. A typical B2B company syncing Salesforce, HubSpot, and a few other SaaS tools to Snowflake pays $500-$2,000/month. Enterprise deployments with large transactional databases can hit $5K-$15K/month. The free tier covers up to 500K monthly active rows.
Fivetran vs Airbyte: which should I use?
Fivetran is fully managed with better reliability and support. Airbyte is open-source with lower costs but requires more engineering to maintain. If you have data engineers and want to minimize cost, Airbyte. If you want zero-maintenance pipelines and can budget for it, Fivetran.
What does Fivetran connect to?
Fivetran has 300+ connectors including Salesforce, HubSpot, Google Analytics, Stripe, PostgreSQL, MySQL, S3, and virtually every major SaaS and database platform. New connectors are added regularly.
Do I need Fivetran if I have Zapier?
Zapier and Fivetran solve different problems. Zapier triggers actions between apps (e.g., 'when a lead is created, notify Slack'). Fivetran syncs entire datasets to a data warehouse for analytics. If you need centralized analytics and reporting, you need Fivetran or something like it. Zapier won't replace a data pipeline.
Our Verdict on Fivetran
Fivetran is the right choice for data and RevOps teams that want reliable, automated data pipelines without dedicating engineering resources to maintenance. The 300+ connector library, automatic schema detection, and managed service model genuinely solve the most painful parts of data pipeline management. If centralized analytics and unified reporting are important to your organization and you don't have data engineers to build custom pipelines, Fivetran is the default choice.
The trade-off is cost and control. Usage-based pricing on high-volume sources can push monthly costs well beyond initial estimates. Teams with data engineering talent and cost sensitivity should evaluate Airbyte — the open-source alternative delivers similar functionality at a fraction of the cost, albeit with more operational overhead. And for simple point-to-point integrations between two SaaS tools, Zapier or Make are far more appropriate and affordable than setting up a Fivetran pipeline.
Fivetran appears in 11 job postings across 8 companies in our database, with an average salary range of $156K-$211K — among the highest in our dataset, reflecting its use by data teams at well-funded companies. It co-occurs most frequently with Looker (4 mentions), confirming the Fivetran→Snowflake→Looker modern data stack pattern. The strong representation of engineering and data roles (5 of 11 postings) versus sales roles confirms Fivetran's positioning as a technical infrastructure tool rather than a front-line sales enablement product.