In today’s data-driven world, organizations face numerous challenges while managing and analyzing vast amounts of data. It becomes more complex to handle large volumes of semi-structured data while integrating data from multiple sources. This often leads to data silos, making it difficult to extract meaningful insights. Fortunately, the MongoDB Atlas to Snowflake integration provides a powerful solution to this problem. 

MongoDB Atlas, a fully managed cloud database service, excels at storing and processing unstructured and semi-structured data. On the other hand, Snowflake, a cloud-native data warehousing platform, offers unparalleled scalability and analytical capabilities. Together, they form a robust ecosystem that addresses the technical challenges associated with data integration.

In this guide, we will explore two easy methods for MongoDB Atlas to Snowflake Data Migration. Let’s dive in!

Method 1: Move Data from MongoDB Atlas Using CSV files

This method of moving data from MongoDB Atlas to Snowflake involves the following steps:

Step 1: Connect your Atlas database to MongoDB Compass

  • Log in to your MongoDB Atlas account. Choose a cluster and click on Connect. Select the Compass version and copy the connection string provided.
  • In the copied connection string, enter your username and password.
MongoDB Atlas to Snowflake: Connect to Cluster
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  • Open MongoDB Compass on your local machine. Paste the modified connection string into the connection field in MongoDB Compass. Click Connect to establish a connection between your application and MongoDB Atlas.

Step 2: Export MongoDB Atlas data as a CSV file

  • In the MongoDB Compass, navigate to the desired cluster’s database. Choose the specific collection you want to export data from.
  • Click on the Export button located at the top right of the screen. A pop-up widget will appear, select the desired format, JSON or CSV, and specify the file location to save the exported document. In this case, we select the CSV file format and click the Export button to initiate the export process.
MongoDB Atlas to Snowflake: Export MongoDB Atlas data as CSV
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Step 3: Upload data to Snowflake

  • Sign in to your Snowsight account, and navigate to the Data > Databases section.
  • Select the specific Snowflake database and schema that contain the table you want to load data into.
  • In the object explorer, choose the desired table and click on Load Data.
  • In the Load Data into Table dialog, select Upload a file and add your CSV file from your local machine.

The manual method is particularly efficient when working with small amounts of data. This makes it a valuable option for smaller businesses or projects.

Limitations of Manually Connecting MongoDB Atlas to Snowflake:

  • Time-Consuming: Manual approach is a time-consuming and resource-intensive process. It involves uploading your Atlas data to the compass, downloading it in CSV format, and then uploading it into Snowflake using snowsight. As the size of data increases, it takes more time to download and upload the files, leading to delays in the overall data transfer.
  • Data Security Risks: Downloading data from one platform and uploading it to another using a CSV file poses potential security risks. Storing sensitive data in an intermediate CSV file increases the risk of unauthorized access. It’s important to ensure proper data protection measures during the manual transfer process to avoid these risks.
  • Real-Time Sync: Manually connecting MongoDB Atlas to Snowflake lacks real-time synchronization. As a result, the data updates in MongoDB Atlas are not immediately reflected in Snowflake. Real-time synchronization would require additional mechanisms such as change data capture (CDC) or automated data integration tools with real-time replication capabilities.

Method 2: Automating the Data Replication Process Using a No-Code Tool

Automating the data replication process using a no-code tool from MongoDB Atlas to Snowflake offers significant advantages over the manual approach. Here are some of them:

  • Drag-and-Drop Functionality: No-code tools often provide a drag-and-drop functionality, allowing you to simplify the data transfer process. These tools eliminate the need for manual coding and technical expertise. This makes integration accessible to non-technical users, democratizing the data transfer process. 
  • Real-Time Data Sync: No-code tools typically offer automated data synchronization capabilities. This means that changes made in Atlas, such as updates, inserts, or deletions, are automatically synchronized with Snowflake in real-time. This ensures that both platforms stay in sync without manual intervention, providing accurate and up-to-date data for analysis.
  • Scalability and Flexibility: No-code tools are designed to scale with growing data volumes and evolving business needs. They offer flexible workflows and configuration options, allowing you to adapt the integration process as your data requirements and workflows change over time.

Hevo Data is a popular no-code tool for automating data replication, offering a simple and intuitive interface for setting up data pipelines. With its pre-built connectors and templates, you can easily configure data replication workflows between MongoDB Atlas and Snowflake without complex coding. 

To migrate data from MongoDB Atlas to Snowflake using Hevo Data, follow these steps:

Step 1: Configure MongoDB Atlas as Source

MongoDB Atlas to Snowflake: Configure Source
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Step 2: Configure Snowflake as Destination

MongoDB Atlas to Snowflake: Configure Destination
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That’s it! You have successfully connected MongoDB Atlas to Snowflake. You can now start analyzing your Atlas data using the powerful capabilities of Snowflake.

Hevo Data is an excellent choice for a no-code data integration tool due to the following reasons:

  • Wide Range of Pre-Built Connectors: With support for 150+ integrations, Hevo enables you to seamlessly connect with a wide range of SaaS applications, payment gateways, advertising platforms, and analytics tools.
  • Drag-and-Drop Functionality: Hevo’s drag-and-drop functionality simplifies transformation tasks like filtering, and mapping, making it perfect for simple and straightforward transformations. For more advanced transformations, you can utilize Hevo’s Python console, which offers extensive libraries and scripting capabilities.
  • Scalability: Hevo Data is built to scale and handle large volumes of data with minimal latency. It has a fault-tolerant architecture that ensures no data loss, and it can handle millions of records per minute as the number of sources and data volume grows.
  • Security and Compliance: Hevo Data is SOC2, GDPR, and HIPAA compliant, providing a secure environment for data integration. This ensures that your data remains protected throughout the integration process.
  • Live Support: Hevo Data offers round-the-clock email, chat, and voice call support. This ensures you can access dedicated support whenever you need assistance with your integration project.

What Can You Achieve by Migrating Data from MongoDB Atlas to Snowflake?

There are numerous benefits of MongoDB Atlas to Snowflake data migration. Here are some of them:

  • Analyzing Individual Interaction Data: By integrating MongoDB Atlas with Snowflake, you can analyze this data at scale, leveraging Snowflake’s analytics capabilities. This lets you gain insights into user behavior, track events, and optimize user experience.
  • Customer Journey Analysis: Centralizing the data would help you get an overview of your customer journey. You can combine different business operations data like sales, marketing, and user engagement to understand the behavioral patterns of your customers.
  • Data Sharing and Collaboration: Snowflake allows you to securely share your data with internal teams, partners, or customers. By migrating MongoDB Atlas data to Snowflake, you can easily share selected datasets with relevant stakeholders, enabling collaborative data analysis or third-party integrations.


Both the manual approach and using a no-code tool for integrating MongoDB Atlas with Snowflake have their advantages. The manual approach provides more control and flexibility for data transformations, while the no-code tool offers time savings, real-time data sync, and scalability. However, for organizations seeking a simplified and efficient MongoDB Atlas to Snowflake integration solution, Hevo Data is an effective choice with its user-friendly interface, 150+ pre-built connectors, real-time data streaming, and data transformation capabilities. Hevo Data empowers you to seamlessly integrate and analyze data from MongoDB Atlas to Snowflake, enabling you to make data-driven decisions with ease.

You can connect your SaaS platforms, databases, etc., to any data warehouse you choose, without writing any code or worrying about maintenance. If you are interested, you can try Hevo by signing up for the 14-day free trial.

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Freelance Technical Content Writer, Hevo Data

Amulya combines her passion for data science with her interest in writing on various topics on data, software architecture, and integration through her problem-solving approach.

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