Are you struggling to perform data integration on your raw data or to create robust data pipelines? Fivetran and Hevo Data are some of the most popular tools for data migration. If you are considering choosing any of these tools, this article is the perfect guide for you. Selecting the right data integration tool is a challenging task, especially when both offer equally competitive services. However, the right tool will not only help save your time but also your resources and expenses. Before comparing Fivetran vs. Hevo Data, let's start by understanding each tool.

What is Hevo Data?

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Hevo Data is a cloud-based data pipeline platform founded in 2017. It specializes in batch and near real-time data integration and streaming capabilities, allowing you to capture with ease. For near real-time replication, Hevo uses  Change Data Capture (CDC), which refers to capturing every change made to data in a database. CDC quickly identifies and modifies data and then moves the changes to the target data warehouse. This ensures your destination has updated data, allowing you to gain insights easily.

Here are some essential features of Hevo Data:

  • Hevo Data supports ETL and ELT processes with the help of its 150+ source and destination connectors.
  • You can apply data transformation on events in two ways—Python scripts or drag-and-drop blocks provided by the Hevo web application.

What is Fivetran?

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Fivetran is a fully-managed, cloud-based data integration platform developed in 2012. With the help of its pre-built connectors, it focuses on automating the data extraction and loading processes from various sources into a centralized data system. This allows organizations to easily access and analyze their data in a unified manner.

Fivetran not only automates data movement but also ensures data security with governance. In terms of privacy, it adheres to industry-standard security practices, such as Column Hashing and Blocking. With column blocking, you can block required columns from replication in your destination. And column hashing allows you to secure Personally Identifiable Information (PII) data from applications before moving it to the target file. This feature reduces the risk of exposing sensitive data and allows you to have more control over your data.

Here are some notable features of Fivetran:

  • Fivetran supports ELT and ETL processes with the help of its 300+ source and destination connectors. While Fivetran does offer some basic transformation features, such as column selection and schema mapping, it allows you to integrate with dbt Core to perform advanced transformations.
  • You can deploy Fivetran connectors either in your private cloud infrastructure or on-premises. This gives you flexibility, security, and control over the location where you want the data integration process to run.

How to Assess Any Data Integration Tool?

Depending on the use case, scalability, and coding capabilities, you can choose to automate the process either on-premises or in the cloud. This section lists the various factors to consider while choosing ETL or ELT tools for your requirements.

  • Data Connectors: Consider listing down the data sources and destinations you require to simplify your work. You can check if the selected platform already offers those connectors; if not, check if it allows you to develop a custom connector. 
  • Use Case: Consider the amount of data at hand before analyzing any tool. Analyze whether you need it for a small or humongous amount of data. Does your business require real-time or batch-driven data analysis? Are the tool pricing plans based on active or updated events or volume of data? These attributes will help you gauge your requirements and provide a better idea about the specific tool you need. 
  • Security: Security is one of the essential factors to consider while selecting any tool. The level of security and governance provided by the tool ensures your sensitive data is protected and shared with the right users.

Hevo Data vs. Fivetran: The Major Differences

While Hevo Data and Fivetran might seem similar, both differ based on use cases. As a result, understanding the differences between Fivetran and Hevo Data is important when choosing the right data integration tool for building your data pipeline. Let's dive into the significant differences between Hevo Data and Fivetran!

Hevo Data vs. Fivetran: Connectors

Hevo Data provides 150+ plug-and-play connectors for file systems, SaaS applications, databases, and more. In case Hevo doesn’t have an in-built connector that you need, you can request their teams to create a custom connector. 

In comparison, Fivetran supports more connectors, which include 10 data warehouses and database destinations and more than 300+ source connectors. Fivetran also offers the flexibility to create a custom connector for your data source or API using its Function Connector. The connector requires you only to write the function to extract source data, and Fivetran manages to load and transform data at your destination.

Hevo Data vs. Fivetran: Security

Hevo Data follows stringent policies regarding your data security and removal retention. Therefore, it ensures the privacy and confidentiality of your data with SOC2, HIPAA, GDPR, and CCPA compliance. It connects to sources and destinations via SSH tunnel, and SaaS sources are encrypted through HTTPS.

On the other hand, Fivetran offers robust security features that include role-based access control (RBAC), SSH, VPN tunnels, and AWS private link. With its security certifications such as GDPR, SOC 2, HIPAA, and PCI DSS, ISO-27001, you can ensure maximum data security.

Both tools provide robust security and compliance to move and analyze data. But if you want specific features like VPN, SSH, column hashing or blocking, and AWS private link, then you should choose Fivetran.

Hevo Data vs. Fivetran: Transformation

Data transformation is the process of converting, cleaning, or transforming data ingested by the source before or after uploading it to the destination. With Hevo Data, there are different approaches to perform data transformation, including in-flight transformation, user-driven transformation, and post-load transformation. Let’s quickly understand all three transformations.

In-flight Transformations: It is used to make lightweight transformations while the data is in transit. For carrying out the in-flight transformation, you have to select the type of transformation you would want while creating the data pipelines. Generally, the In-flight transformation includes table and column name sanitization, compression, JSON parsing in the destination, converting dates to timestamps in UTC format, adding meta fields, and filtering unrequired fields.

User-driven Transformation: Hevo also has the option to perform the transformation on the data before it is loaded into the destination system, known as User-driven transformation. This includes data cleaning, filtering, deduplication, normalization, re-expressing, and data enrichment that can be applied to ensure data quality.

Post-data Transformation: In addition to In-flight and User-driven, Hevo also supports Post-data transformation, which enables you to further refine and transform data after it has been loaded into the destination. This can be achieved using SQL queries. Post-load transformation enables you to perform advanced analytics and apply complex transformations based on your specific use cases or requirements.

On the other hand, Fivetran only has a few transformation capabilities. Some of them are data normalization, schema migration, data types mapping, schema mapping, built-in data deduplication, and dynamic schema change support. However, for complex transformation, Fivetran supports Data Build Tool (dbt). With dbt, you can either use Python or SQL to write transformation models within the data warehouse. 

Hevo Data vs. Fivetran: Reverse ETL

Hevo supports reverse ETL through Hevo Activate. It helps you to extract data from your destination and sync it back to your operational systems or third-party applications. In simple terms, Reverse ETL enables you to take the transformed data stored from your data warehouse and send it back to your operational systems. This can be useful for scenarios where your marketing data would help make better sales through CRM. With Hevo Activate, you can turn your analytics into action by syncing data back to the systems that drive your business.

Fivetran, on the other hand, doesn’t support reverse ETL.

Hevo Data vs. Fivetran: Pricing

Hevo Data provides an event-based pricing model and custom pricing solutions on its pricing plans. Event-based pricing relies on each updated or inserted record in the destination and is counted as one event. The plans are divided into three packages—Free, Starter, and Business.

Free: This plan includes 50+ connectors, and you can insert or update events upto one million.

Starter: This plan offers a 14-day free trial with access to 150+ connectors with monthly and yearly subscriptions.

For more detailed information on a Business plan, look into Hevo Data pricing plans.

On the other hand, Fivetran provides users with monthly and annual subscriptions on all plans. It has volume-based pricing plans and charges on monthly active rows, which means you only pay for monthly active rows. Fivetran includes five different pricing plans which are suitable from startups to global enterprises.

Starter: Using this plan, you can easily automate data movement for your applications and files. This plan includes automatic schema migrations and integration for dbt core.

Standard: The Standard plan covers all the features of the Starter plan and is designed for unlimited users. It syncs your data from your source to your destination every 15 mins. You can also access Fivetran's REST API in this plan.

Enterprise: This plan is suitable if you want to access high-volume agent connectors and Oracle. It syncs once every 5 minutes. This plan offers advanced security features, including VPN tunnels, data governance, and granular RBAC for teams.

Business Critical: You can select this plan if you require the highest levels of data protection and compliance. The Business Critical plan offers customer-managed keys for encryption to manage data.

Private Deployment: To achieve secure database replication and control of data, you can deploy Fivetran on-premises, in a virtual private cloud, or on your secure network. To know more about its detailed features, visit Fivetran’s pricing plan.

Estuary Flow: A Real-Time Data Integration & ETL Solution

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Estuary Flow is one of the robust data integration alternatives that help you streamline and automate your ELT workflows efficiently. With its intuitive UI and code-free approach, it eliminates the need for intricate coding, allowing you to perform data migration tasks without demanding extensive programming skills.

Some of the amazing features of Estuary include:

  • Many to many ETL: Unlike Hevo or Fivetran, Estuary Flow not only supports ELT. It enables many-to-many real-time or batch ETL, with multiple sources and targets in the same pipeline, and streaming transformations.
  • Connectors: With a wide support of pre-built source and destination connectors, Estuary provides robust solutions for various data integration requirements. Its sources and destination connectors cover popular data warehouses, SaaS applications, databases, and APIs.
  • Scalability: It can handle massive datasets with a capacity of up to 7GB/s. This enables seamless data transfer for operations from small data sets to enormous at terabytes scale.
  • Exactly-once Semantics: Estuary is built on Gazette, similar to Kafka, offering exactly-once processing semantics. This eliminates the necessity of de-duplicating real-time data.
  • CDC: It uses CDC (Change Data Capture) to capture and deliver data changes in real-time. This allows you to have up-to-date and synchronized data across the system. CDC technique is especially valuable for applications that require real-time analytics, reporting, or synchronization between different data sources.
  • Automatic Schema Handling: As an automated service, Flow takes care of data mapping and schema handling. It infers into the schema source changes and automatically maps them to the destination, allowing you to focus on other critical tasks.

Estuary Flow has also proven itself to be one of the most cost-effective solutions, with 2x lower vendor costs and 2-4x greater data engineering productivity.

Here’s a comprehensive comparison table outlining differences between Hevo Data, Fivetran, and Estuary Flow:


Hevo Data


Estuary Flow

Connectors (Source and Destination)



150+ from Estuary Support for 500+ Airbyte, Stitch, and Meltano connectors

Custom Connector






Hevo API docs


Fivetran Rest API docs


Estuary API docs


Drag-and-drop and Python 

dbt with Python or SQL integration

SQL and JavaScript




Data Source Authentication

OAuth / HTTPS / SSH / SSL / API Tokens

OAuth / API Keys

OAuth 2.0 / API Tokens


Both Fivetran and Hevo Data provide incredible data integration solutions but cater to different use cases. Each tool serves unique features and capabilities to ease the data movement process in organizations with greater efficiency, speed, and accuracy. While Hevo is the optimal solution for lightweight ETL reverse ETL workloads, Fivetran is best suited for businesses that want ELT capabilities. However, if you want complex transformation and have custom requirements, Fivetran with dbt is the go-to solution.

So, assess your requirements carefully and select the right tool that fits best for your business needs. Since both tools provide free trials, you can check which one will be the most comfortable for your workload.

But if you want a more real-time, flexible, and scalable data pipeline for your voluminous data requirements, get in touch with Estuary Flow. With its real-time integration, data security, and pipeline resilience, Flow is more advantageous. Sign up today to try your first free pipeline.

Looking for more insights into data integration solutions?  Dive Deeper into comparisons between Hevo Data and other leading platforms by exploring these blogs: 

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