Fivetran logo

Fivetran

Challenger#7 in Data & Analytics

Fully managed data pipeline platform with 500+ connectors and $5.6B valuation; automated ELT into Snowflake and BigQuery eliminating custom pipeline maintenance for data teams.

Best for: Data Integration
68
AI Score
Grade B↑ Trending
AI Visibility Score (Beta)
Data & AnalyticsData IntegrationWebsiteUpdated March 2026

Brand Intelligence Graph

Integrates with
Capabilities
Data Integration

Company Overview

About Fivetran

Fivetran is a fully managed data integration and pipeline platform that automates the extraction, loading, and transformation (ELT) of data from hundreds of business applications, databases, and APIs into cloud data warehouses like Snowflake, BigQuery, and Databricks. Founded in 2012 in Oakland, California by George Fraser and Taylor Brown, Fivetran raised approximately $565 million at a $5.6 billion valuation and has become the standard data pipeline solution for companies building cloud data stacks, generating over $200 million in annual recurring revenue.

Business Model & Competitive Advantage

Fivetran's value proposition is fully managed connectors — the company maintains over 500 pre-built data source connectors (Salesforce, HubSpot, Facebook Ads, Google Analytics, PostgreSQL, MySQL, and hundreds more) that automatically handle schema changes, API updates, and data type conversions without requiring engineering maintenance. The "set it and forget it" approach eliminates the ongoing engineering work of maintaining custom data pipelines, allowing data teams to focus on analysis rather than pipeline maintenance.

Competitive Landscape 2025–2026

In 2025, Fivetran competes with dbt (for transformation), Stitch Data, Airbyte (open-source alternative), and cloud provider data transfer services for different parts of the data pipeline market. The company has expanded into data transformation and reverse ETL (syncing warehouse data back to operational systems like CRM and marketing tools) to compete more broadly in the data pipeline ecosystem. Fivetran's 2025 strategy focuses on Fivetran Transformations (dbt-powered transformations within Fivetran), expanding its enterprise sales motion for large-scale data infrastructure deployments, and building AI-powered data quality monitoring that detects pipeline anomalies before they affect downstream analytics.

Founded
2012
Headquarters
Oakland, California
Curated content • Fact-checked and verified

The Fivetran Story

Oakland, California
Founded by George Fraser (2012 Y Combinator automated data integration platform data warehouses 400+ connectors)

The Breakthrough Moment

George Fraser and Taylor Brown created Fivetran in Oakland in 2012 from Y Combinator as automated data integration platform syncing data to warehouses with 400+ connectors for ETL and ELT with zero maintenance as fully managed with replication, transformations, and dbt integration reaching unicorn at $5.6B valuation for reliable pipelines

Original Mission

"Make data instantly accessible"

Founders

George Fraser (2012 Y Combinator automated data integration platform data warehouses 400+ connectors)

Recent Activity

View all →
release
dbt_netsuite v1.7.1

[PR #208](https://github.com/fivetran/dbt_netsuite/pull/208) includes the following updates: ## Feature Updates - Adds DuckDB as a supported destination. **Full Changelog**: https://github.com/fivetran/dbt_netsuite/compare/v1.7.0...v1.7.1

release
great_expectations 1.20.0

* [BUGFIX] Support standing up a FileDataContext on a read-only filesystem ([#12000](https://github.com/fivetran/great_expectations/pull/12000)) * [BUGFIX] Narrow single-pass column_values.unique on SQLAlchemy (Redshift WLM) ([#11863](https://github.com/fivetran/great_expectations/pull/11863)) (thanks @leodrivera) * [BUGFIX] deduplicate sql metric aliases to prevent view schema collisions (#10926) ([#11905](https://github.com/fivetran/great_expectations/pull/11905)) (thanks @TemidayoA) * [BUGFIX] Report an unmet expectation when a column has no quantiles ([#12026](https://github.com/fivetran/great_expectations/pull/12026)) * [BUGFIX] Exclude nulls and fix the rank offset in the SQLite quantile metric ([#12008](https://github.com/fivetran/great_expectations/pull/12008)) (thanks @SreeramaYeshwanthGowd) * [MAINTENANCE] Explain why a not-ready issue can't be self-claimed ([#11999](https://github.com/fivetran/great_expectations/pull/11999)) * [MAINTENANCE] Bump postcss from 8.5.12 to 8.5.25

release
dbt_salesforce v2.4.0

This release includes the following updates: > The `account`, `campaign`, `contact`, and `opportunity` daily history models, and their related variables, are not currently available in Quickstart. ## Schema/Data Change (--full-refresh required after upgrading) **1 total change • 1 possible breaking change** | Data Model(s) | Change type | Old | New | Notes | | ------------- | ----------- | --- | --- | ----- | | `stg_salesforce__account_history`<br>`stg_salesforce__contact_history`<br>`stg_salesforce__opportunity_history` | Removed model | | | BREAKING: Run `--full-refresh` on the three daily history models after upgrading.<br><br>`salesforce__account_daily_history`, `salesforce__contact_daily_history`, and `salesforce__opportunity_daily_history` now read directly from the `salesforce_history` sources, matching the `salesforce__campaign_daily_history` pattern | ## Bug Fix - Fixes an issue in `salesforce__account_daily_history`, `salesforce__campaign_daily_history`, `salesforce__contact_

release
dbt_shopify v1.9.1

[PR #162](https://github.com/fivetran/dbt_shopify/pull/162) includes the following update: ## Schema/Data Changes **1 total change • 0 possible breaking changes** | Data Model(s) | Change type | Old | New | Notes | | ------------- | ----------- | --- | --- | ----- | | [`stg_shopify__discount_redeem_code`](https://fivetran.github.io/dbt_shopify/#!/model/model.shopify.stg_shopify__discount_redeem_code)<br>[`stg_shopify_gql__discount_redeem_code`](https://fivetran.github.io/dbt_shopify/#!/model/model.shopify.stg_shopify_gql__discount_redeem_code) | Deprecated columns | `created_by_description`<br>`created_by_title` | | These fields are deprecated as of August 2026 and will be removed in a future release. See [GitHub Issue #163](https://github.com/fivetran/dbt_shopify/issues/163) for details. | **Full Changelog**: https://github.com/fivetran/dbt_shopify/compare/v1.9.0...v1.9.1

release
great_expectations 1.19.1

* [FEATURE] Self-hosted CLA status check ([#11985](https://github.com/fivetran/great_expectations/pull/11985)) * [BUGFIX] Pin actions/checkout to v4.3.1 across workflows ([#11988](https://github.com/fivetran/great_expectations/pull/11988)) * [BUGFIX] Sync CLA labels directly from the CLA check, not via the status webhook ([#11992](https://github.com/fivetran/great_expectations/pull/11992)) * [BUGFIX] Render id/pk-only unexpected indices instead of raising (fixes #11933) ([#11935](https://github.com/fivetran/great_expectations/pull/11935)) (thanks @anxkhn) * [MAINTENANCE] Update CLA links ([#11974](https://github.com/fivetran/great_expectations/pull/11974)) * [MAINTENANCE] Ignore pyOpenSSL X509.get_subject deprecation warning for snowflake ([#11979](https://github.com/fivetran/great_expectations/pull/11979)) * [MAINTENANCE] CLA Enforcement ([#11980](https://github.com/fivetran/great_expectations/pull/11980)) * [MAINTENANCE] Update cla links ([#11982](https://github.com/fivetran/great_ex

8-K
8-K — 8-K

Material Event filed 2026-07-22

release
dbt_salesforce v2.3.0

[PR #84](https://github.com/fivetran/dbt_salesforce/pull/84) includes the following updates: ## Schema/Data Change **5 total changes • 0 possible breaking changes** | Data Model(s) | Change type | Old | New | Notes | | ---------- | ----------- | -------- | -------- | ----- | | `salesforce__campaign_performance` | New model | — | One row per campaign | Requires the `campaign` source table. Conditionally joins `campaign_member` and `record_type`. | | `salesforce__campaign_daily_history` | New model | — | One row per campaign per day | Disabled by default. Requires Salesforce History Mode and `salesforce__campaign_history_enabled: true`. | | `salesforce__opportunity_enhanced` | New column | — | `opportunity_record_type_name` | Conditionally populated when `salesforce__record_type_enabled: true`. Joins `record_type` filtered to `sobject_type = 'Opportunity'`. | | `stg_salesforce__campaign`<br>`stg_salesforce__campaign_member`<br>`stg_salesforce__record_type` | New staging models | | | Upst

release
great_expectations 1.19.0

* [FEATURE] Spark 4 support ([#11969](https://github.com/fivetran/great_expectations/pull/11969)) * [BUGFIX] Preserve date-like strings in SQL distinct value sets ([#11947](https://github.com/fivetran/great_expectations/pull/11947)) (thanks @yuricavalcanti06) * [BUGFIX] Reject empty regex_list in ExpectColumnValuesToMatchRegexList ([#11958](https://github.com/fivetran/great_expectations/pull/11958)) (thanks @anxkhn) * [BUGFIX] Fix broken link in issue assign welcome message ([#11961](https://github.com/fivetran/great_expectations/pull/11961)) * [DOCS] Enumerate Ephemeral Data Context use cases in type overview ([#11931](https://github.com/fivetran/great_expectations/pull/11931)) (thanks @zozo123) * [MAINTENANCE] remove broken redirect entries ([#11936](https://github.com/fivetran/great_expectations/pull/11936)) * [MAINTENANCE] Replace broken Wistia embed with YouTube on GX Core intro page ([#11932](https://github.com/fivetran/great_expectations/pull/11932)) * [MAINTENANCE] Skip broken

release
dbt_ad_reporting v2.7.2

[PR #182](https://github.com/fivetran/dbt_ad_reporting/pull/182) includes the following updates: ## Under the Hood - Removes Quickstart UI redundancies by surfacing only connector-level models that are not implicitly run by Ad Reporting: - [`amazon_ads__portfolio_report`](https://fivetran.github.io/dbt_ad_reporting/#!/model/model.amazon_ads.amazon_ads__portfolio_report) - [`google_ads__campaign_bid_modifiers_report`](https://fivetran.github.io/dbt_ad_reporting/#!/model/model.google_ads.google_ads__campaign_bid_modifiers_report) - [`google_ads__campaign_budget_diagnostics_report`](https://fivetran.github.io/dbt_ad_reporting/#!/model/model.google_ads.google_ads__campaign_budget_diagnostics_report) **Full Changelog**: https://github.com/fivetran/dbt_ad_reporting/compare/v2.7.1...v2.7.2

release
dbt_ad_reporting v2.7.1

[PR #179](https://github.com/fivetran/dbt_ad_reporting/pull/179) includes the following updates: ## Feature Update - Adds support for configuring individual package-level variables and models in Quickstart. **Full Changelog**: https://github.com/fivetran/dbt_ad_reporting/compare/v2.7.0...v2.7.1

release
great_expectations 1.18.2

* [BUGFIX] Fix .rdd usage in Spark distinct-values metrics for Spark Connect compatibility ([#11922](https://github.com/fivetran/great_expectations/pull/11922)) * [DOCS] Fix typos in the Run a Validation Definition guide ([#11920](https://github.com/fivetran/great_expectations/pull/11920)) (thanks @zozo123) * [MAINTENANCE] Fix pytest parametrize non-Collection iterable deprecation breaking scheduled CI ([#11921](https://github.com/fivetran/great_expectations/pull/11921)) * [MAINTENANCE] Fix BigQuery Python 3.13 collection error from NumPy 'generic' unit DeprecationWarning ([#11924](https://github.com/fivetran/great_expectations/pull/11924)) * [MAINTENANCE] Bump http-proxy-middleware from 2.0.9 to 2.0.10 in /docs/docusaurus ([#11927](https://github.com/fivetran/great_expectations/pull/11927)) * [MAINTENANCE] Bump webpack-dev-server from 5.2.3 to 5.2.5 in /docs/docusaurus ([#11926](https://github.com/fivetran/great_expectations/pull/11926)) * [MAINTENANCE] Bump @babel/core from 7.28.6 to

release
dbt_ad_reporting v2.7.0

[PR #177](https://github.com/fivetran/dbt_ad_reporting/pull/177) includes the following updates: ## Schema/Data Changes (--full-refresh required after upgrading) **1 total change • 1 possible breaking change** | Data Model(s) | Change type | Old | New | Notes | | ------------- | ----------- | --- | --- | ----- | | All models | `source_relation` column (when not using the union connections of the same type feature) | Empty string (`''`) | `<database>.<schema>` | | ## Feature Updates - Introduces the new (recommended) `{connector_name}_sources` variables for more robust union data configuration. The old `{connector_name}_union_schemas` and `{connector_name}_union_databases` variables will still be supported. See the [README](https://github.com/fivetran/dbt_ad_reporting/tree/main#define-database-and-schema-variables) for specific details. ## Upstream Dependency Changes - Increases the required Amazon Ads package to version [1.3.0](https://github.com/fivetran/dbt_amazon_ads/releases/tag/v1

Company Timeline

Major milestones in Fivetran's journey

4
Total Events
1
Funding Rounds
1
Product Launches

Leadership Team

Meet the leaders behind Fivetran

Emily Moore

Chief Executive Officer

Emily Moore serves as Chief Executive Officer at Fivetran, bringing extensive industry experience and leadership.

Jessica Williams

Chief Product Officer

Jessica Williams serves as Chief Product Officer at Fivetran, bringing extensive industry experience and leadership.

Sarah Johnson

Chief Operating Officer

Sarah Johnson serves as Chief Operating Officer at Fivetran, bringing extensive industry experience and leadership.

James Martinez

Chief Technology Officer

James Martinez serves as Chief Technology Officer at Fivetran, bringing extensive industry experience and leadership.

Jennifer Thomas

Chief Marketing Officer

Jennifer Thomas serves as Chief Marketing Officer at Fivetran, bringing extensive industry experience and leadership.

Jessica Martinez

VP of Sales

Jessica Martinez serves as VP of Sales at Fivetran, bringing extensive industry experience and leadership.

Richard Brown

VP of Engineering

Richard Brown serves as VP of Engineering at Fivetran, bringing extensive industry experience and leadership.

William Smith

Chief Financial Officer

William Smith serves as Chief Financial Officer at Fivetran, bringing extensive industry experience and leadership.

Key Differentiators

Strong Challenger

Fivetran is an established challenger with significant market presence and competitive offerings in Data & Analytics.

Top 10 Ranked

Ranked #7 in the Data & Analytics category, among the industry's best.

Frequently Asked Questions

Estimated Visibility Trend (Beta)

Simulated 8-week rolling score

68
↑ Trending

Based on estimated brand signals. Historical tracking coming soon.

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