Replicate data to any of your cloud-based destinations

Seamlessly manage data replication from your SaaS applications and databases to your destination of choice with Fivetran.

  • Easy implementation in just a few clicks
  • Fully managed data replication
  • Complete end-to-end automation

Amazon S3

An object storage service offering industry-leading scalability, data availability, security and performance.

Fivetran partner
Data lake

Azure Data Lake Storage

A cloud-based, scalable data storage solution for big data analytics. ADLS allows you to store and manage massive amounts of data in any format.

Fivetran partner
Data lake

Azure Synapse

A petabyte-scale data warehouse that separates compute and storage activities. Compute nodes use the SQL Server database engine and data is stored in Azure Blob Storage.

Fivetran partner


Google’s serverless, petabyte-scale data warehouse for analytics performed using standard SQL queries.

Fivetran partner


An open-source storage layer that brings reliability to data lakes. Databricks provides ACID transactions, scalable metadata handling and unifies streaming and batch data processing that is fully compatible with Apache Spark APIs.

Fivetran partner


A transactional database that supports small-scale analytics use cases and destination-to-destination loads from data that has been transformed in a data warehouse.



A transactional database that can ingest transformed data or be used as a data warehouse for small-scale use cases.



A fully managed, petabyte-scale cloud data warehouse where compute and storage are combined in database nodes within a Redshift cluster.

Fivetran partner


A logical cloud data warehouse that separates compute and storage where syncs take the entire schema from the source and replicate it into Snowflake.

Fivetran partner
Data cloud

SQL Server

A transactional database meant for small-scale use cases and to ingest transformed data for sharing across business units.


Apache Kafka

An open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration and mission-critical applications.

Event platform

Find the right type of data storage for your business

A successful data strategy depends on choosing the right
 approach to storing your data.

Data lake

Supports the movement of large quantities of unstructured and semi-structured data via batch processes or streaming

Serves as a centralized repository for data from many teams and functions within a business

Lowers the total cost of ownership for data pipelines versus storing the data in the source system

Quickly performs analyses on your data via dashboards, visualizations and machine learning

Data warehouse

Ingests structured data from relational databases, transactional systems, cloud applications and many other sources

Organizes data into tables structured by the schema from the source system and in the case of Fivetran using type inference

Typically architected to have fast performing storage for frequently accessed data and slower storage for archival data

Analyses can be performed on the data and processed within the warehouse for rapid findings in business intelligence tools

Alternative popular storage methods

A database is an organized collection of data stored in a computer. The most common types store data in rows and columns in a series of tables. This makes storing, managing and retrieving the data you need easier.

Learn more
Streaming platform

Platforms like Apache Kafka are used for streaming analytics, data integration and mission-critical applications. Teams looking for the highest throughput and to store streams of data safely in a distributed, durable, fault-tolerant cluster turn to storage via Kafka.

Learn more
Trusted by thousands of data-driven companies

Data movement that is fast, powerful and cost effective

Fivetran takes a thoughtful approach to replicating your data to minimize your compute costs and operate efficiently, including:

Type inference

Fivetran infers the necessary data type for all of our supported destinations to ensure that syncs run accurately and successfully.

Schema and table management

Fivetran creates, delivers and manages the base tables in your destination and checks against our internal representation of the table to identify any schema changes in the source.

Long value truncation

Fivetran will natively truncate string fields or throw an error message for JSON and binary fields if the length is longer than the accepted length in the destination.

Accelerate your data movement today

Join thousands of companies using Fivetran to centralize and transform their data.

Start a trial