COMPARISON

Dataddo vs. Fivetran

Dataddo and Fivetran are both market-proven data integration tools, and which one is right for your use case will depend on a range of factors.

This comparison will help you make an informed decision based on your specific requirements.

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Pricing
Based on	No. of data flows A data flow is the connection between a source and a destination. For example, a connection between Facebook Ads and Looker Studio would count as one flow.	No. of data rows
Free plan
Integration Types
Dashboards as destinations
Data warehouses as destinations
Apps as destinations (reverse ETL)
Features
Data warehouse required?	No Though Dataddo can connect to any data warehouse, it also allows users to store data in its embedded SmartCache.	Yes
Time to add new connectors	10 days	Must be coded by users
Coding required?	No	Yes, for transformations
Platform does transformations?	Yes Dataddo automatically cleanses and harmonizes data before sending it to a destination. This makes it immediately analyzable in dashboards, and easier for engineers to manipulate in data warehouses.	No
Encryption	In-transit & at-rest	In-transit & at-rest
24/7 customer support

VERSUS

Pricing

Fivetran’s pricing is active row-based. This could be beneficial for small businesses or startups moving lower volumes of data, but keep in mind that your bill will fluctuate in accordance with how much data you move.

Dataddo’s pricing is flow-based. What is a data flow? The connection between a source and a destination, e.g., Facebook Ads to BigQuery, would count as one flow. This means your bill will be the same every month (unless you decide to scale up or down, which can be done easily).

Both vendors offer a limited free plan.

Connectors

Fivetran offers a wide portfolio of connectors, but if the one you need isn’t on their list, you'll need to build it yourself.

Dataddo also offers a wide portfolio of connectors. If the one you need isn’t on our list, we'll create it for you in about two weeks.

Integration Types

Fivetran supports ELT operations and database replication. It does not support reverse ETL operations, but it cooperates closely with Census, a company that does.

Dataddo also supports ELT and database replication, but, in addition, it supports ETL, reverse ETL, and direct end-to-end integration of online sources with dashboarding apps. This comprehensive integration functionality makes it possible for users to send data from literally any source to any destination.

Data Transformation/Customization Capabilities

Fivetran does not have any native transformation functionality, but it integrates closely with dbt—a data transformation platform for data engineers. For non-dbt users, Fivetran provides a selection of pre-built transformation templates (also courtesy of dbt) for common data transformation scenarios. Whether you use the templates or dbt itself for transformations, the transformations take place in the warehouse.

Dataddo offers a blend of pre-built and custom transformation capabilities. It provides an easy-to-use, visual interface where users can define custom transformations, significantly reducing reliance on SQL. This makes the platform more inclusive for teams with varying technical proficiencies. Dataddo users can still use dbt as a layer on top of their warehouse, so there is no “forced” system of transformations. Also, because Dataddo pre-cleans any data it extracts, and because it enables exclusion of unnecessary data like personal identifiable information (PII) from datasets, it saves on warehouse fees and solves the majority of data security issues right at the extraction level.

If you really want to fully customize your business logic, both Fivetran and Dataddo offer “headless” products. Fivetran offers a partial REST API, while Dataddo offers a full REST API.

Ease of Use

Fivetran is designed for use by data engineers and data scientists. Its functionality therefore requires a certain level of technical proficiency, and using the tool involves a learning curve, especially for users unfamiliar with data integration and SQL. Technically oriented teams or those with the resources to invest in learning the platform will be pleased with the depth of capabilities and granularity of control it offers.

Dataddo places a strong emphasis on user experience, aiming to combine power and simplicity. It offers an intuitive, no-code user interface designed to minimize the learning curve for non-technical users and save work for engineers, making it accessible to a wide range of users. It offers visual aids for data transformations and straightforward methods for setting up and managing data flows. This is good for teams with a mix of technical skills or for businesses aiming to democratize data usage across different departments.

Inbuilt Data Quality Mechanisms

Fivetran approaches data quality by focusing on error handling and reporting. Its platform is designed to alert users when data pipeline issues arise, including discrepancies in data, sync failures, and broken connectors. It also offers a history mode, which enables users to analyze data from a certain point in time, or how their data has changed over time (on a per-table basis). Connector log data is retained for one week; longer retention requires integration with an external logging service. In general, Fivetran relies on users' initiative to monitor these alerts and take corrective actions.

Dataddo takes a multi-layered approach to data quality. Among other mechanisms, it features a built-in anomaly detector and filtering system, which lets users set rule-based integration triggers that prevent suspicious datasets from flowing downstream. It also incorporates data validation checks during extraction and transformation stages to ensure data integrity, as well as a notification system to alert users of any issues. The connector and flow logs give users a complete overview of all activity within the tool. Dataddo’s engineers also proactively monitor and maintain pipelines independently of user initiative, minimizing the need for user intervention.

Data Warehouse: Necessary or Not?

Fivetran specializes in the extraction of data to warehouses, so you have to have a data warehouse in order to use it.

Dataddo specializes in the same, but, in addition, it allows you to skip the warehouse and extract data straight to dashboarding apps, which is useful for business teams that need quick insights. In case your business doesn’t have a warehouse, you can use Dataddo’s embedded SmartCache to collect data from periods past.

Security

Both Fivetran and Dataddo are certified and/or compliant with SOC 2 Type 2, ISO 27001, and other global and regional standards for data privacy and security.

Additionally, Dataddo is compliant with the Digital Operational Resilience Act (DORA) - Regulation (EU) 2022/2554.

Both Fivetran and Dataddo offer security features like data hashing/masking, SSH tunnelling and reverse SSH tunnelling, single sign-on (SS), exclusion of personal identifiable information (PII) from extractions, and AWS/Azure/Google Cloud private link capabilities.

Support

It’s hard to give a point-by-point comparison of support for two SaaS products unless you’re a paying customer of both. So, in this section, we’ll not speak to Fivetran support, but instead talk about what Dataddo has to offer.

In a word, Dataddo support is world-class. We offer live support around the clock, and our team of engineers proactively monitors pipelines and handles API changes. Our documentation is thorough and clear, and our Solutions Architects are ready to take a personal interest in your use case.

Have special implementation requirements? No problem. We can provide a tailored support package that includes expert consultancy, guided planning, and flexible licensing, to ensure that your data integration initiatives are a success.

But don’t take our word for it—go to any software review website and see what our customers are saying!

Pricing

Pay as You Grow

Billed monthly

Billed annually ~25% OFF

What is a data flow?

A data flow is the connection between a data source or sources and a destination. For example, if you send data from Facebook Ads (source) to Looker Studio (destination), this will count as one flow.

Learn More

Supported integration types

How Do You Want to Move Your Data?

END to END

Data from Apps » Dashboarding Apps

Send data from cloud services straight to dashboarding apps or Google Sheets.

ETL ETLT ELT

Data from Apps » Data Warehouses

Move data from cloud services to storages to establish one source of truth for all decisions.

REVERSE ETL

Data from Warehouses » Apps

Send data back into apps to give business teams insights in the systems they use most.

ETL

Database Replication

Connect storages to replicate, migrate, and distribute data throughout your organization.

Testimonials

Dataddo Is Ranked #1 by Customers