What is Fivetran: Deep Dive on Features, Use Cases, Pricing, & the Best Alternative

The ETL market hit $10.24 billion in 2026 and is projected to reach $21.25 billion by 2031. That implies a change in how companies think about data. Companies now want to move the right data to the right place, automatically, without a team of engineers babysitting every pipeline.

Here’s the thing, though. Automating data pipelines sounds straightforward until you’re three months in and your data team is still debugging broken schemas.

Tools like Fivetran and Hevo promise to solve this, pull data from wherever it lives (Salesforce, Shopify, PostgreSQL, you name it), load it into a warehouse like Snowflake or BigQuery, and keep it fresh. 

But fully managed doesn’t mean fully identical. The details matter more than any feature list will tell you.

In this guide, we’ll take an honest, detailed look at Fivetran: what it does well, where it stumbles  and why Hevo might be the better fit for your team.

What is Fivetran?

Fivetran is a fully managed data pipeline platform that automates data integration from source to destination. It helps businesses move data from various sources into a centralized data warehouse without needing to write or maintain complex code.

Imagine your company uses Salesforce for sales, Stripe for payments, HubSpot for marketing, and PostgreSQL for product data. You want all that data in one place, so your analysts and data scientists can build dashboards, run models, or track KPIs.

Doing this manually? Painful. Time-consuming. Prone to errors.

That’s where Fivetran comes in:

• Extracts data from your source systems (apps, APIs, databases)
• Loads it into your data warehouse
• Automatically updates it on a regular schedule (every 15 minutes on Standard, down to 1 minute on Enterprise)
• Handles schema changes on its own; if a field is added or renamed in the source, Fivetran adapts without breaking your pipeline

Fivetran follows the ELT (Extract, Load, Transform) approach, meaning raw data is loaded first, and transformation happens inside your warehouse. This has become the standard pattern for a modern data team. Since compute inside the warehouse is cheap and scalable, so why not let it do the heavy lifting?

Since its all-stock merger with dbt Labs in October 2025, Fivetran now combines data movement and transformation under one roof. The merged entity is led by George Fraser (CEO) and Tristan Handy (President). They’ve also absorbed Census (reverse ETL) and Tobiko Data (SQLMesh and SQLGlot) in the same year. It’s an aggressive consolidation play of owning the entire data pipeline lifecycle.

Whether that consolidation benefits users or creates vendor lock-in is an open question. We’ll come back to it.

Want to know more about Fivetran’s track record? Don’t miss our detailed Fivetran review blog.

How Fivetran Works?

Fivetran is a kind of data delivery service that runs on autopilot. You point it at where your data is and where you want it, the platform handles the rest. Here’s the step-by-step breakdown:

Connect to Your Sources

Fivetran offers 500+ pre-built connectors for SaaS apps, databases, file storage, event streaming, and more. You log into your Fivetran dashboard, pick a source (say, Shopify or Google Ads), authenticate it, and you’re done. Each connector includes built-in configuration tips and a step-by-step setup guide.

If your data source isn’t in the catalog, you can build a custom connector using Fivetran’s Connector SDK (Python 3.13), which still supports core features like data blocking and resyncing.

Extract the Data

Fivetran uses APIs or log-based CDC (Change Data Capture) to pull data from the source. It syncs only what’s new or changed (this is called incremental sync) which saves both time and compute. For databases, CDC-based extraction captures row-level changes from transaction logs, making it far more efficient than full-table scans.

Load It Into Your Warehouse

Once the data is extracted, Fivetran loads it directly into your data warehouse, like Snowflake, Redshift, BigQuery, or Databricks. As of 2026, Fivetran supports 31+ destinations, including newer additions like ClickHouse, Oracle, and even vector databases like Milvus.

It uses the ELT approach:

• Extract: pull data from source
• Load: land it in the warehouse as-is
• Transform: reshape, filter, or join data inside the warehouse

This means heavy data processing happens where compute is cheapest and most scalable.

Schema Mapping and Auto-Updates

Fivetran automatically normalizes and maps your source schema into tables and columns in your destination. If your source schema changes (say, a new field is added in Salesforce) Fivetran detects it and adapts without breaking the pipeline.

That’s a genuine win for data engineers who’ve spent weekends fixing pipelines that broke because a source app pushed a schema change nobody anticipated.

Sync on a Schedule

You can set sync frequency anywhere from every 5 minutes to every 24 hours, depending on your plan. The default is every 6 hours, but most paid plans support 15-minute intervals, and Enterprise plans go as low as 1 minute.

Transformation (Post-Merger with dbt)

With the dbt Labs merger, Fivetran now integrates directly with dbt Core (versions 1.9.10 and 1.10.11 as of 2026) and Coalesce for in-warehouse transformations. You also get prebuilt transformation models for common use cases. The first 5,000 monthly model runs are free; beyond that, usage-based pricing applies.

Check out our blogs on Fivetran vs Matillion and Fivetran vs Stitch to see how Fivetran compares with other tools.

Fivetran Connectors

One of Fivetran’s biggest strengths is its connector library. With 500+ pre-built connectors, you can pull data from virtually any modern tool in your stack.

These connectors handle the tedious work, including data extraction, API management, schema adaptation and consistent syncing. When a source platform pushes an API update, Fivetran updates the connector automatically.

Types of Fivetran Connectors

Fivetran organizes its connectors into a number of categories:

Connector Type	Examples	Typical use case
SaaS Apps	Salesforce, HubSpot, Google Ads, Stripe	Sync CRM, marketing, and payment data into your warehouse
Databases	MySQL, PostgreSQL, MongoDB, SQL Server	Centralize operational data for analytics
Cloud Functions	AWS Lambda, Azure Functions	Ingest event-based or serverless data
Event Streaming	Kafka, AWS Kinesis	Stream high-volume real-time data
File Storage	S3, Google Drive, Dropbox	Pull in spreadsheets, CSVs, and log files
Analytics Tools	Google Analytics 4, Mixpanel	Merge web/product analytics with business data

You can also check our blog on Fivetran HVR for additional information.

Where the Connectors Fall Short

Fivetran’s connector library is broad, but it’s not without its flaws. Here are the recurring complaints from real users:

1. Beta connectors can be unreliable

Several G2 reviewers have flagged that some connectors, particularly newer or less popular ones, are still in beta and lack full functionality. 

Pricing can be a barrier for early-stage startups or companies with unpredictable data volumes. Since Fivetran charges based on monthly active rows (MAR), costs can spike unexpectedly as your data grows—even if you’re not increasing the number of sources. Additionally, some niche connectors are still in beta or lack full functionality, and the granularity of scheduling could be more flexible (e.g., custom cron instead of fixed intervals).

Dennis C.

Head of Business Operations

View Review

One Capterra reviewer noted that dbt integration packages with Fivetran “seem to have multiple issues.” If you depend on a niche connector, test it thoroughly before committing.

2. Limited customization

Fivetran is opinionated about how it structures data in your warehouse; super-normalized schemas that don’t always match how your team wants to query data. This rigidity can be frustrating for engineering teams that want granular control over data modeling.

Sync times can cause issues with business processes if you need to start at a particular time multiple times a day. Choices are limited for users and sync times consistently change (i.e every hour does not have the ability to start on the hour but at a fivetran determined start time). Package integrations with DBT seem to have multiple issues, although Fivetran does offer office hours with support staff to assist. Would be nice to see a price breakdown for monthly MAR in addition to just the # of records.

Kristin

Business Systems Manager in US

View Review

3. One-directional only

Fivetran moves data from source to destination. If you need bidirectional sync (for example, writing enriched data back to Salesforce), you’ll need the separate Activations product, which launched with its own MAR pricing curve. It’s not included by default.

Currently, Fivetran offers only one direction data sync. Having both directional sync would be awesome.

Verified Reviewer

View Review

4. Enterprise database connectors are gated

Connectors for Oracle, SAP, and certain high-volume agent sources require the Enterprise or Business Critical plans. If you’re on the Standard plan, you simply don’t get access — and upgrading isn’t cheap.

Pricing can be a barrier for early-stage startups or companies with unpredictable data volumes. Since Fivetran charges based on monthly active rows (MAR), costs can spike unexpectedly as your data grows—even if you’re not increasing the number of sources. Additionally, some niche connectors are still in beta or lack full functionality, and the granularity of scheduling could be more flexible (e.g., custom cron instead of fixed intervals).

Dennis C.

Head of Business Operations

View Review

Before picking Fivetran, check out how it compares with other tools: Fivetran vs Airflow.

Fivetran Pricing

Fivetran’s pricing has been changed significantly and the changes haven’t gone over well with everyone.

The Pricing Model: Monthly Active Rows (MAR)

Fivetran’s pricing is based on Monthly Active Rows (MAR), which is the number of unique rows inserted or deleted in your destination warehouse each month. A row is counted only once per month, even if it syncs multiple times.

Last year, Fivetran shifted from account-level MAR to connector-level MAR billing. Previously, your total MAR across all connectors was aggregated to determine your pricing tier, so higher total volume meant better rates. Now, each connector is billed on its own independent cost curve. For teams running many connectors with moderate volume each, this eliminated bulk discounts and led to cost increases that some users describe as 2x to 4x higher than before.

As of January 2026, deletes also count toward paid MAR (they didn’t before), and each standard connection carries a $5 monthly minimum charge (not applicable to the Free plan).

Current Plans (2026)

Free Plan

• Up to 500,000 MAR/month
• Up to 5,000 model runs for transformations
• Limited connector access
• Best for: Small teams testing the platform

Standard Plan

• Access to 500+ connectors
• 15-minute sync frequency
• dbt Core integration, SSH tunnels, RBAC

Enterprise Plan

• Everything in Standard plus 1-minute syncs
• Enterprise database connectors and high-volume agent connectors
• Hybrid deployment option

Business Critical Plan

• Everything in Enterprise plus customer-managed encryption keys
• Private networking
• PCI DSS Level 1 certification

What Companies Actually Pay

According to Vendr data, the median annual spend on Fivetran is approximately $44,681/year, with enterprise organizations spending around $115,000/year after negotiated discounts. Buyers report an average 17% savings through negotiation.

The Hidden Cost Problem

Beyond the listed tiers, several factors inflate your actual bill:

• Full refreshes and backfills can spike your MAR unexpectedly. 
• Transformation costs are separate; each successful model run counts, including intermediate models in the job graph. Complex dbt projects can generate thousands of runs per month.
• Annual contracts offer 5% to 22% discounts but require a $12,000/year minimum commitment.
• Connector-level pricing means you can no longer offset a high-volume connector’s cost by bundling it with lower-volume ones.

For more comparisons, check out: Fivetran vs Talend, Fivetran vs Striim, Fivetran vs MuleSoft, Fivetran vs Workato, Fivetran + dbt + Snowflake stack, Fivetran FAQs, and Fivetran Support.

Fivetran Reviews: What Customers Are Saying

We dug through hundreds of verified reviews on G2, Capterra, and Gartner Peer Insights to identify the patterns. Here’s what keeps coming up: both the good and the bad.

Top 3 Pros

1. Ease of Setup and Use

This is Fivetran’s most praised quality, cited in 200+ G2 mentions. Connectors are plug-and-play. 

Fivetran excels at doing one thing incredibly well: reliably syncing data from multiple SaaS tools into a central data warehouse like BigQuery. The setup is remarkably fast—most connectors are essentially plug-and-play, with minimal configuration. I especially appreciate the wide connector library, automatic schema management, and robust alerting system. For a small team without a full-time data engineer, it’s a game-changer. It eliminates a ton of manual work and lets us focus on deriving insights rather than wrangling APIs.

Dennis C.

Head of Business Operations

One G2 reviewer noted that Fivetran “excels at doing one thing incredibly well: reliably syncing data from multiple SaaS tools into a central data warehouse.” This matters a lot for small teams without a full-time data engineer.

2. Connector Breadth and Reliability

Fivetran has 500+ connectors covering SaaS apps, databases, file storage, and event streams. Multiple reviewers highlight that once a connector is set up, it works as intended; automated schema handling and incremental syncs reduce the ongoing maintenance burden to near zero. 

Fivetran makes data integration incredibly easy. Setting up connectors takes only minutes, and the automated pipelines handle schema changes seamlessly. The sync process is fast and reliable, and the documentation and UI make it straightforward to monitor jobs. Whenever I had questions, the support team was responsive and helpful, making adoption smooth.

Hayk C.

VP of Data

View Review

3. Automatic Schema Management

When your source data structure changes, Fivetran adapts without breaking the pipeline. This is a feature data engineers rarely appreciate until they’ve experienced the alternative. As of March 2026, Fivetran introduced automatic re-sync detection to ensure data consistency after connection drops or schema changes.

Top 3 Cons

1. Pricing That Spirals at Scale

This is the number-one complaint people have with Fivetran. On G2’s pros-and-cons page, “Expensive” has 46 mentions and “Pricing Issues” has 28. 

Since the 2025 shift to connector-level billing, costs have become harder to predict and significantly more expensive for teams running multiple connectors. 

2. Limited Customization and Transformation Options

Fivetran is great if you want a hands-off experience. But you’ll hit walls if your team needs to customize how data is shaped or modeled before it lands in the warehouse.

It would be great to have more detailed logging, when there is an issue it is some times hard to diagnose the cause without contacting support. Likewise, it would be great to be able to configure the query batch size (which by default is 10M rows), or to automatically adjust that based on the table size (GiB and row count), because right now if you have a table with ~10M rows but very large size, it can stall the historical sync process or require extremely large statement timeout settings.

Verified Reviewer

View Review

The dbt merger will eventually help here but the built-in transformation capabilities remain limited compared to platforms that let you transform before, during and after loading.

3. Support Can Be Hit-or-Miss

While some users praise Fivetran’s support, others report slow responses and a lack of proactive communication during critical incidents. 

Pricing transparency. Fivetran is very opaque about pricing. Daily summaries of row usage by table are provided, but we often incur large charges where Fivetran is unable to explain why those charges were incurred. The lack of pricing auditability is a big issue.

Eric A.

Chief Data Officer

Want a deeper analysis? Read our full Fivetran review. 

Also see: Fivetran pitfalls and troubleshooting Fivetran sync delays.

How Does Hevo Do It Better?

Fivetran is a good product. It pioneered automated data pipelines, and its connector library is the deepest in the market. But good doesn’t mean it’s right for everyone,  and the areas where Fivetran falls short happen to be the areas where Hevo is strongest.

With the Fivetran + dbt Labs merger tightening integration across data movement and transformation, some teams appreciate the consolidation. Others see it as a path toward vendor lock-in. There would be fewer choices and more dependence on a single vendor’s roadmap. Hevo takes the opposite approach: keep your stack modular and don’t penalize you for growing.

Here’s specifically how Hevo addresses the pain points Fivetran users keep raising.

Transparent, Predictable Pricing

Fivetran’s connector-level MAR billing has made cost forecasting genuinely difficult for teams with multiple data sources.

Hevo uses event-based pricing with tiered plans

• Free: Up to 1M events/month 
• Starter: Starting at $239/month for 5M events (annual billing)
• Professional: Starting at $679/month for up to 100M events
• Business Critical: Custom pricing for enterprise needs

All connectors are included on paid plans. You know what you’re paying before the month ends.

Check out Hevo’s pricing page for full plan details.

Real-Time Data Pipelines 

Fivetran’s standard sync frequency is 15 minutes. If you want 1-minute syncs, that’s an Enterprise plan feature and significantly more expensive. And even 1-minute syncs aren’t truly real-time; they’re fast batch processing.

Hevo offers streaming pipelines on its Professional and Business Critical plans, with no additional per-feature charges. That is a meaningful difference if you need fresh data for real-time dashboards or AI model inputs, this is a meaningful difference.

Customer Success Story: Postman

The team at Postman needed real-time insights from product usage data to optimize user experience and improve retention. After switching to Hevo, they built real-time dashboards in hours instead of days and enabled product teams to make faster data-backed decisions.

Enterprise-Grade Reliability

Hevo recently rebuilt its core engine around the fundamentals of reliability, simplicity and transparency. The platform now runs on a microservices-based architecture where ingestion, orchestration, and loading operate as isolated and independently scalable services. The result is 20x to 40x faster data movement and fault isolation that prevents one pipeline failure from cascading into others.

The platform now offers two connector tiers within the same UI

• Standard Connectors for SaaS and mid-scale workloads
• Enterprise Connectors with dedicated per-pipeline compute, advanced CDC extraction, and batch-level verification

You can run both side by side, without any forced migration.

More Control Over Transformations

Hevo gives you more flexibility by letting you transform before, during, or after loading:

• Apply Python-based custom logic in the pipeline
• Use drag-and-drop transformations for no-code workflows
• Run dbt, SQL, and Hevo Transformer jobs together
• Handle complex data flattening (JSON, nested fields) inside the pipeline itself

This flexibility helped Postman automate user event enrichment by identifying power users directly in their warehouse without extra scripts or tools.

24/7 Live Support

Hevo offers 24/7 live chat and email support to all users, including those on free trials. If your team needs help during integration, Hevo’s engineers will respond immediately. There is no SLA escalation involved.

No Vendor Lock-In

Hevo integrates with dbt, supports 150+ connectors across SaaS apps and databases and much more and works with every major warehouse. If you ever want to switch transformation tools or orchestration layers, your pipelines don’t break.

Sign up for a 14-day free trial with Hevo and see the difference for yourself. 

If you’re considering the switch from Fivetran, Hevo offers a contract buyout program and a Fivetran migration checklist to make the transition smooth.

FAQs