Sold by: Fivetran
Amazon Redshift, Databricks, Snowflake, and S3 data lake in matter of a minutes. Fivetran's no-code platform offers organizations of all sizes, across all industries, a simple, flexible way to move data from hundreds of data sources with 99.9% uptime.
4.3
Overview
Fivetran automatically centralizes your data from hundreds of SaaS application databases -- both open source and on-premises -- into your AWS environment including Amazon Redshift, Databricks, Snowflake, and S3 data lake in a matter of minutes. Fivetran's no-code data movement platform offers organizations of all sizes, across all industries, a simple flexible way to move data from hundreds of data sources with 99.9% uptime.
With the Census acquisition, Fivetran now offers reverse ETL as well, helping organizations move transformed, enriched data back to business applications to operationalize and activate data. Currently, Census may only be purchased through private marketplace offers. Fivetran brings industry-leading security and compliance, cost efficiency, and ease of use to AWS destinations, such as Amazon S3 and Redshift. When combined, Fivetran's data integration and reverse ETL and AWS's robust data storage destinations unlock exceptional opportunities for near real time decision making with limitless potential for future growth. By choosing Fivetran, customers can leverage these capabilities to avoid technical complexity and meet governance standards to support data lake adoption at scale. Our fully-managed pipelines are highly available with zero-maintenance so that you can focus on analyzing your data, understanding your customers, and improving your product.
After subscribing through AWS Marketplace, customers will be redirected to our registration page to complete the onboarding process. This includes providing key information required for automation in our system. Once completed, customers will be directed to a secondary page to generate their unique Account ID, which is necessary for accessing Fivetran's services.
Highlights
- Managed Data Lake Service designed to automate and standardize your data ingestion into Amazon S3
- 5-minute setup, zero-configuration, and zero-maintenance data movement pipelines for hundreds of data sources with 99.9% uptime
- Gain full control over your data movement with Fivetran's advanced security and governance capabilities
Details
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Features and programs
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month | Overage cost |
|---|---|---|---|
Standard Plan | Pay-As-You-Go, Actual Usage, see features at fivetran.com/pricing | $0.01 | |
Enterprise Plan | Pay-As-You-Go, Actual Usage, see features at fivetran.com/pricing | $0.01 |
Dimension | Description | Cost/unit |
|---|---|---|
overages | Fivetran Platform Overages | $0.01 |
Dimensions summary
This listing bills through a contract with three usage-based dimensions. You pick either the Standard Plan or the Enterprise Plan, both charged by actual usage on a pay-as-you-go basis. Usage is measured in units tied to the data you move, transform, and activate each month. The Overages dimension covers any consumption beyond your committed contract amount. Your spend rate declines as your monthly volume rises, so the two plans differ in rate and included capabilities rather than in billing method. All three dimensions consolidate into one contract.
Top-of-mind questions for buyers
Usage is measured in monthly active rows (MAR), meaning the distinct primary keys synced in a billing period. A row counts once per period even if it syncs multiple times. Inserts, updates, and deletes count. Unchanged rows in re-syncs and the initial bulk load do not count.
Consumption past your committed contract amount is billed through the Overages dimension. This lets your data movement continue without interruption. Your spend rate still declines as monthly volume rises, so the per-unit rate applied to that extra usage follows the same declining curve as your plan.
Three activities meter usage: connections that move data, transformations that run data models, and activations that push data to destinations. Each is priced separately on its own declining cost curve. All three consolidate into one contract. Connections and activations bill on MAR; transformations bill on successful monthly model runs.
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SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
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Support
Vendor support
Additional support resources available at fivetran.com/docs Support offered 24/7 via support@fivetran.com .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
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Negative reviews
AI generated from product descriptions
No-Code Data Integration Platform
Automated data movement from hundreds of SaaS applications, databases, and on-premises sources without requiring code configuration
Multi-Destination Support
Data ingestion capability to Amazon Redshift, Databricks, Snowflake, and S3 data lakes
High Availability and Uptime
99.9% uptime service level agreement with fully-managed, zero-maintenance pipelines
Reverse ETL Functionality
Capability to move transformed and enriched data back to business applications for data operationalization and activation
Security and Governance Controls
Industry-leading security and compliance features with advanced governance capabilities for data movement control
Automated Schema Management
Automatically detects and applies source schema changes to the destination schema without manual intervention
Pre-load and Post-load Transformations
Supports on-the-fly data formatting and cleaning through pre-load transformations, and SQL-based transformations with dbt Core model execution through post-load transformations
Multi-source Data Integration
Connects to 150+ data sources including SQL, NoSQL, and SaaS applications for centralized data replication
Security and Compliance
Complies with HIPAA, SOC 2, and GDPR standards with secure connection options including SSH, Reverse SSH, and VPN
Supported Data Sources
Supports 140+ data sources including Postgres, MySQL, Google Analytics, Shopify, and Salesforce
Cloud Data Destinations
Integrates with cloud destinations including Amazon Redshift, Amazon S3, and Snowflake
Schema Change Adaptation
Automatically adapts to source schema changes without requiring manual pipeline modifications
Field-Level Data Configuration
Enables configuration of data syncs at the field level to capture only required data
Change Data Capture
Captures incremental changes to ensure analytics systems work with the latest data
Standard contract
No
No
No
Customer reviews
RAM K.
Fast, Time-Saving Data Pipelines in Minutes
Reviewed on Oct 07, 2026
Review provided by G2
What do you like best about the product?
It helps us land data in the destination within a couple of minutes, which would otherwise take a data engineer a significant amount of time to build a pipeline for.
What do you dislike about the product?
There’s no way to deselect a CDC table from the selection. This option was available at the beginning, but now we don’t want to sync that table anymore. Since CDC was removed in between, the table no longer shows up in Fivetran, so we can’t deselect it.
What problems is the product solving and how is that benefiting you?
Managing schema drift and identifying hard deletes in Source
Gautam Ashish G.
Reliable, User-Friendly MongoDB-to-Snowflake Syncs That Save Engineering Time
Reviewed on Oct 06, 2026
Review provided by G2
What do you like best about the product?
What I like most about Fivetran is its reliability and ease of use, especially for ingesting MongoDB data into Snowflake. The data syncs consistently and accurately, and I have faced very few issues while using it.
The UI is intuitive and user-friendly, making it easy to set up connectors, monitor syncs, and troubleshoot when required. I also particularly like how Fivetran handles MongoDB's nested data and unnesting, which makes working with complex MongoDB structures much simpler.
Another major advantage is the ability to run transformations within Fivetran, allowing us to manage ingestion and transformation workflows in one platform.
From a Pricing / ROI perspective, I find the platform valuable because it significantly reduces the engineering effort required to build and maintain custom ingestion pipelines. The support and onboarding experience has also been helpful when setting up and working with connectors.
Finally, the increasing use of AI and intelligence features is a positive addition, as it helps make data engineering workflows more automated and efficient.
Overall, Fivetran provides a good combination of reliability, usability, automation, and reduced maintenance overhead, which is why it has been a strong choice for our data ingestion and transformation needs.
The UI is intuitive and user-friendly, making it easy to set up connectors, monitor syncs, and troubleshoot when required. I also particularly like how Fivetran handles MongoDB's nested data and unnesting, which makes working with complex MongoDB structures much simpler.
Another major advantage is the ability to run transformations within Fivetran, allowing us to manage ingestion and transformation workflows in one platform.
From a Pricing / ROI perspective, I find the platform valuable because it significantly reduces the engineering effort required to build and maintain custom ingestion pipelines. The support and onboarding experience has also been helpful when setting up and working with connectors.
Finally, the increasing use of AI and intelligence features is a positive addition, as it helps make data engineering workflows more automated and efficient.
Overall, Fivetran provides a good combination of reliability, usability, automation, and reduced maintenance overhead, which is why it has been a strong choice for our data ingestion and transformation needs.
What do you dislike about the product?
There are not many major issues from my experience with Fivetran. One area that could be improved is the pricing, especially as data volumes and the number of connectors grow, since the overall cost can increase significantly over time.
For MongoDB, while the ingestion and unnesting capabilities work very well, some advanced configurations and transformation workflows could be made more intuitive and easier to manage directly through the UI. More intelligent recommendations around schema changes, transformation optimization, and monitoring would also make the platform even more useful.
That said, the reliability and the amount of engineering effort it saves largely offset these concerns in my experience.
For MongoDB, while the ingestion and unnesting capabilities work very well, some advanced configurations and transformation workflows could be made more intuitive and easier to manage directly through the UI. More intelligent recommendations around schema changes, transformation optimization, and monitoring would also make the platform even more useful.
That said, the reliability and the amount of engineering effort it saves largely offset these concerns in my experience.
What problems is the product solving and how is that benefiting you?
Fivetran significantly simplifies the process of ingesting and maintaining data pipelines, especially for our MongoDB-to-Snowflake use case. Instead of building and maintaining custom ingestion pipelines, we can configure a connector and let Fivetran handle the syncing, schema changes, and data movement reliably.
The MongoDB unnesting capabilities are particularly useful because they make complex and nested MongoDB data much easier to work with in Snowflake. The syncing has been very consistent in my experience, with minimal issues and very little manual intervention required.
The UI also makes it easy to configure connectors, monitor syncs, identify issues, and troubleshoot when needed. Fivetran's transformation capabilities further help us prepare and transform the data without having to build everything from scratch.
Overall, it reduces engineering and maintenance effort, improves reliability, and allows the team to focus more on analytics and business use cases rather than managing data pipelines. The time saved and reduced operational overhead provide good ROI for us.
The MongoDB unnesting capabilities are particularly useful because they make complex and nested MongoDB data much easier to work with in Snowflake. The syncing has been very consistent in my experience, with minimal issues and very little manual intervention required.
The UI also makes it easy to configure connectors, monitor syncs, identify issues, and troubleshoot when needed. Fivetran's transformation capabilities further help us prepare and transform the data without having to build everything from scratch.
Overall, it reduces engineering and maintenance effort, improves reliability, and allows the team to focus more on analytics and business use cases rather than managing data pipelines. The time saved and reduced operational overhead provide good ROI for us.
Sabrina F.
Easy, Intuitive, and Integrates Smoothly with Our Systems
Reviewed on Oct 05, 2026
Review provided by G2
What do you like best about the product?
It's super easy and intuitive. It has a very specific function and it's very good at doing the function. It integrates with all of the systems we use and is easy to get them configured so the initial setup.
What do you dislike about the product?
Just the price pretty much. Besides that it does everything I would want it to do.
What problems is the product solving and how is that benefiting you?
We have data that comes in from all different sources. With fivetran we are able to ingest that data and put it in one centralized location (snowflake) and then be able to see and use all of our data in one spot. Before fivetran, we had made custom pipelines that we would have to dedicate a lot of time to for debugging and maintenance.
Mickey v.
Strong Control Over Data Ingestion and Activations
Reviewed on Oct 05, 2026
Review provided by G2
What do you like best about the product?
It helps us maintain control over our data ingestion and activations.
What do you dislike about the product?
Some connectors don’t include all the fields or objects I need, which ends up requiring two connectors: one standard connector and one SDK connector.
What problems is the product solving and how is that benefiting you?
Nice integrations with dbt.
Financial Services
Everything We Need: Strong HubSpot Integration, Clear UI/UX, Helpful Support
Reviewed on Oct 05, 2026
Review provided by G2
What do you like best about the product?
The hubspot integration has everything we need. The ui/ux is also understandable and we got all our answers easily from support chat or documentation.
What do you dislike about the product?
There was some confusion at first on how the fields are propagated for the integration, but we found the answer
What problems is the product solving and how is that benefiting you?
Syncing data from hubspot back to our database. It gives us clear insights about sales activities.