Fivetran
Data Ingestion

What is Fivetran

Fivetran is a cloud-based data integration platform that simplifies and accelerates the process of centralizing and syncing data from various sources into a data warehouse, providing a streamlined approach to data pipeline management.

Why choose Fivetran

01

Automated Data Pipeline

Fivetran offers more automation options than other tools, fully handling the extraction, transformation, and ETL process, making it very easy to use and streamlining the workflow.

02

Cloud-agnostic

Fivetran is cloud-agnostic, allowing users to choose the data warehouse of their preference, whether it's Google BigQuery, Snowflake, Amazon Redshift, or others.

03

Data cleaning

Fivetran automatically looks for duplicate entries, incomplete data and incorrect data, simplifying yet another step in the process of Data Analysis.

04

Schema Management

The platform handles schema changes automatically, adapting to modifications in source systems without disrupting the data pipeline.

05

Synchronization

Fivetran supports real-time data synchronization. It offers data blocking to ensure sensitive data protection, making it easy to omit tables or fields users do not want to sync to the destination warehouse.

Fivetran interface

Modern data stack

Fivetran Alternatives

Frequently asked questions

What does Fivetran do and do we need it?

Fivetran automates data ingestion — pulling data from 300+ sources (databases, SaaS tools, APIs) into your warehouse. If you spend more than 5 hours/month maintaining custom data pipelines, Fivetran pays for itself.

Fivetran vs Airbyte — which should we choose?

Fivetran: enterprise reliability, 300+ connectors, zero maintenance. Airbyte: open-source, cheaper, 350+ connectors but requires self-hosting. Choose Fivetran if you value reliability over cost savings.

How much does Fivetran cost?

Fivetran prices by monthly active rows (MAR). Starter plan begins at $1/credit. Most startups with 5-10 connectors spend $500-2,000/month. High-volume sources like event data can increase costs significantly.

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