No-code pipeline · MongoDB → Amazon S3

Send data from MongoDB to Amazon S3

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From MongoDB to Amazon S3: managed, scheduled, no code.

Kondado automatically replicates MongoDB collections and views to Amazon S3 on a configurable schedule, converting document-based data into structured files that data teams can query immediately using standard SQL engines.

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Replicate MongoDB Data to Amazon S3 Automatically

Kondado provides a direct integration between MongoDB and Amazon S3, allowing you to replicate your NoSQL data to scalable cloud storage without writing code. Configure your data source once, select which collections and views to replicate through available pipelines, and set your preferred update frequency ranging from every few minutes to daily intervals. Your MongoDB data arrives in Amazon S3 structured and ready for analysis with Athena, Presto, or Dremio.

Once your data lands in Amazon S3, you can combine it with information from other sources to build comprehensive analytics workflows. Whether you are preparing data for Power BI, Looker Studio, or creating data lakes for machine learning projects, Kondado handles the extraction and loading so you can focus on generating insights.

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The Collections & Views pipeline automatically maps all your MongoDB collections and views, ensuring your document structure is preserved when replicated to Amazon S3. This means your product catalogs, user sessions, and transaction logs become immediately available as queryable files in your data lake.

With your MongoDB data in Amazon S3, you can run complex aggregations using Amazon Athena or join NoSQL data with relational sources from PostgreSQL or BigQuery to create unified business reports. Data teams use this replicated data to power custom dashboards, feeding cleaned and transformed JSON documents directly into visualization tools without manual export processes.

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Replicated to Amazon S3

Dynamic data

Kondado automatically reads the schema of your MongoDB. All tables, views, and fields available in your account are extracted without manual configuration.

available pipeline

Amazon S3

Destination

What Kondado extracts

Collections & Views

Kondado automatically maps all collections and views in your database

See all available data → Send MongoDB to Amazon S3 →

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How to send MongoDB data to Amazon S3

Sync data automatically — no code, no manual exports.

Connect your MongoDB data source

Provide your MongoDB connection details or Atlas connection string to establish a link between your database and Kondado. The platform automatically detects available collections and views, displaying all replicateable pipelines for your selection.

Configure your Amazon S3 destination

Enter your AWS credentials and specify the target S3 bucket where your MongoDB data should land. You can organize data by setting custom prefixes and folder structures to maintain logical separation between different collections or business units.

Select collections and set schedule

Choose which MongoDB collections and views to replicate from the available pipelines, then define your update frequency ranging from 5 minutes to daily intervals. Kondado will begin automated replication according to your schedule, delivering fresh data to Amazon S3 ready for analysis with SQL engines or visualization in Power BI and Looker Studio.

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Send data from MongoDB to other destinations

MongoDB > Looker Studio

MongoDB > Power BI

Other visualizations

MongoDB > Amazon S3

MongoDB > BigQuery

MongoDB > Excel

MongoDB > Google Sheets

MongoDB > MySQL

MongoDB > PostgreSQL

MongoDB > Redshift

MongoDB > SQL Server

Choose a tool to visualize your MongoDB data

If the software you need is not listed, drop us a messagem. You can use almost every tool

MongoDB > Airtable

MongoDB > Alteryx

MongoDB > Amazon Quicksight

MongoDB > BIMachine

MongoDB > Cortex

MongoDB > Data Studio

MongoDB > Geckoboard

MongoDB > Grafana

MongoDB > IBM Cognos Analytics

MongoDB > Klipfolio

MongoDB > Looker Studio

MongoDB > Looker

MongoDB > Looqbox

MongoDB > Metabase

MongoDB > Microstrategy

MongoDB > Pentaho

MongoDB > Power BI

MongoDB > Qlik Cloud Analytics

MongoDB > Qlik Sense

MongoDB > Qlik

MongoDB > QlikView

MongoDB > Redash

MongoDB > Superset

MongoDB > Tableau

MongoDB > BI TOTVS

MongoDB > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending MongoDB data to Amazon S3 automatically

How does Kondado replicate data from MongoDB to Amazon S3? ▼

Kondado connects to your MongoDB instance using your connection credentials, then extracts selected collections and views based on your configured schedule. The platform transforms document-based data into structured file formats before loading them into your designated Amazon S3 bucket, maintaining data relationships and schema consistency throughout the process.

What MongoDB data can I replicate to Amazon S3? ▼

You can replicate any collections and views from your MongoDB databases, including those hosted on MongoDB Atlas. The pipeline automatically detects all available collections in your database, allowing you to select specific datasets like user profiles, event logs, or product inventories without writing custom extraction scripts.

How often can I update my MongoDB data in Amazon S3? ▼

Kondado offers flexible scheduling options ranging from near-real-time updates every 5 minutes to hourly, daily, or custom intervals. You configure the replication frequency based on your business needs, ensuring your Amazon S3 data lake stays current without overwhelming your MongoDB production environment with excessive read operations.

What file format does MongoDB data arrive in when sent to Amazon S3? ▼

Your MongoDB documents are converted into structured file formats optimized for analytics engines like Amazon Athena, Presto, and Dremio. This conversion preserves nested JSON structures while making the data queryable through standard SQL syntax, enabling seamless integration with your existing business intelligence stack.

Can I combine MongoDB data with other sources after it reaches Amazon S3? ▼

Yes, once your MongoDB data resides in Amazon S3, you can join it with datasets from PostgreSQL, BigQuery, or other sources also replicated through Kondado. This capability allows you to create comprehensive reports that correlate NoSQL documents with relational records in Power BI or Looker Studio.

Do I need to manually map MongoDB collections before replicating to Amazon S3? ▼

No manual mapping is required because Kondado automatically discovers all collections and views in your MongoDB database. The platform handles schema detection and conversion automatically, creating corresponding structures in Amazon S3 that reflect your original document organization while optimizing for analytical query performance.

Can I use MongoDB Atlas with Kondado's Amazon S3 pipelines? ▼

Yes, Kondado supports both self-hosted MongoDB instances and MongoDB Atlas cloud deployments. Simply provide your Atlas connection string when configuring the data source, and Kondado will establish the pipeline to replicate your Atlas collections to Amazon S3 on your chosen schedule.

Try out all the features for free for 14 days

Related on Kondado

Try out all the features for free for 14 days