
Move your data from Amazon S3 with your free account
Capture data from Amazon S3 and deliver it to your destinations using Estuary's pre-built connectors. Build pipelines for real-time, incremental, or batch data movement based on connector capabilities.
- <100ms to batch
- 200+ connectors
- Managed data pipelines



Amazon S3 connector details
Estuary’s Amazon S3 connector captures and processes data from your S3 buckets or prefixes, automatically converting files into Estuary collections for downstream analytics and integration. It supports incremental ingestion of new or updated objects and automatically detects multiple data formats for flexible file-based pipelines.
- Continuously ingests data from S3 buckets or specific prefixes
- Supports CSV, JSON, Avro, and other formats with automatic schema detection
- Enables incremental syncs using lexicographic key ordering for efficiency
- Securely connects using AWS IAM roles or access keys
- Backed by Estuary’s private deployment and VPC security options for controlled access
How to connect Amazon S3 to your destination in 3 easy steps
- 1
Connect Amazon S3 as your data source
Securely connect Amazon S3 and choose the objects, tables, or collections you need to sync.
- 2
Prepare and transform your data
Apply transformations and schema mapping as data moves whether you are streaming in real time or loading in batches.
- 3
Deliver to your destination
Continuously or periodically deliver your data to the destination you choose, based on the capabilities and configuration of your pipeline.
Learn more with some related videos
Dive deeper into Amazon S3 with tutorials and walkthroughs from our YouTube channel.
![How to Load Data into Apache Iceberg (S3 + Glue Tutorial) video thumbnail]()
How to Load Data into Apache Iceberg (S3 + Glue Tutorial)
Learn about the Apache Iceberg table format, why it’s essential for organizing your data lake, and how to load data into Iceberg using Estuary. We’ll cover a brief intro to Iceberg before demoing the connector setup with Estuary, Amazon S3, and AWS Glue for real-time and batch data integration.
![Streaming Data Lakehouse Tutorial: MongoDB to Apache Iceberg video thumbnail]()
Streaming Data Lakehouse Tutorial: MongoDB to Apache Iceberg
Learn how to connect MongoDB to Apache Iceberg in Iceberg table format using Estuary. In this step-by-step demo, we show you how to:
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All data connections are fully encrypted in transit and at rest. Estuary also supports private cloud and BYOC deployments for maximum security and compliance.
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HIGH THROUGHPUT
Distributed, event-driven architecture scales for demanding data workloads.
DURABLE COLLECTIONS
Store data as it moves so you can transform, replay, and deliver it downstream.
FLEXIBLE LATENCY
From <100ms CDC and real-time streaming to scheduled batch, depending on connector capabilities.
From <100ms to batch
Estuary supports CDC, real-time streaming, incremental syncs, and scheduled batch across its connector ecosystem. Capture data from Amazon S3 using the cadence supported by the connector, then transform and deliver it to the destinations your team uses.
- Connect Amazon S3 to warehouses, databases, data lakes, search platforms, and event systems through Estuary-supported destinations.
- Capture once and reuse Amazon S3 data across transformations and multiple downstream destinations without rebuilding source extraction.
Don't see a connector?Request and our team will get back to you in 24 hours
Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
| Estuary | Batch ELT/ETL | DIY Python | Kafka | |
|---|---|---|---|---|
| Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
| Latency | <100ms to scheduled | 5min+ | Varies | <100ms |
| Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
| Scale | ||||
| Maintenance Effort | Low | Medium | High | High |
One platform for real-time and batch data pipelines

Deliver real-time and batch data from DBs, SaaS, APIs, and more

Popular sources/destinations you can sync your data with
Choose from more than 100 supported databases and SaaS applications. Click any source/destination below to open the integration guide and learn how to sync your data in real time or batches.
![Apache Iceberg Logo]()
Apache Iceberg
![Databricks Logo]()
Databricks
![MotherDuck Logo]()
MotherDuck
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MySQL
![Amazon Redshift Logo]()
Amazon Redshift
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Snowflake
![Elastic Logo]()
Elastic
![Google Bigquery Logo]()
Google Bigquery
![HubSpot Logo]()
HubSpot
![Dremio Logo]()
Dremio
![AWS OpenSearch Logo]()
AWS OpenSearch
![Amazon EventBridge Logo]()
Amazon EventBridge
![Amazon SNS Logo]()
Amazon SNS
![Google Bigtable Logo]()
Google Bigtable
![ClickHouse Logo]()
ClickHouse
![Bauplan Logo]()
Bauplan
![Google Spanner Logo]()
Google Spanner
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SingleStore
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Supabase
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Azure Blob Storage Parquet
![RisingWave Logo]()
RisingWave
![Materialize Logo]()
Materialize
![Imply Polaris Logo]()
Imply Polaris
![ClickHouse Kafka API Logo]()
ClickHouse Kafka API
![Bytewax Logo]()
Bytewax
![SingleStore Dekaf Logo]()
SingleStore Dekaf
![StarTree Logo]()
StarTree
![Tinybird Logo]()
Tinybird
![Azure Fabric Warehouse Logo]()
Azure Fabric Warehouse
![Dekaf Logo]()
Dekaf
![Apache Kafka Logo]()
Apache Kafka
![Amazon S3 Iceberg (delta updates) Logo]()
Amazon S3 Iceberg (delta updates)
![Google Cloud Storage CSV Logo]()
Google Cloud Storage CSV
![Google GCS Parquet Logo]()
Google GCS Parquet
![Amazon S3 CSV Logo]()
Amazon S3 CSV
![Amazon RDS for PostgreSQL Logo]()
Amazon RDS for PostgreSQL
![Amazon RDS for SQL Server Logo]()
Amazon RDS for SQL Server
![Amazon RDS for MariaDB Logo]()
Amazon RDS for MariaDB
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Amazon RDS for MySQL
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Google Cloud SQL for SQL Server
![Google Cloud SQL for PostgreSQL Logo]()
Google Cloud SQL for PostgreSQL
![Google Cloud SQL for MySQL Logo]()
Google Cloud SQL for MySQL
![Oracle MySQL Heatwave Logo]()
Oracle MySQL Heatwave
![Amazon Aurora for MySQL Logo]()
Amazon Aurora for MySQL
![MariaDB Logo]()
MariaDB
![Amazon DynamoDB Logo]()
Amazon DynamoDB
![SQL Server Logo]()
SQL Server
![HTTP Webhook Logo]()
HTTP Webhook
![Pinecone Logo]()
Pinecone
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Slack
![Azure Cosmos DB Logo]()
Azure Cosmos DB
![Amazon Aurora for Postgres Logo]()
Amazon Aurora for Postgres
![SQLite Logo]()
SQLite
![MongoDB Logo]()
MongoDB
![Alloy DB for Postgres Logo]()
Alloy DB for Postgres
![Timescale Logo]()
Timescale
![Google PubSub Logo]()
Google PubSub
![Google Sheets Logo]()
Google Sheets
![Amazon S3 Parquet Logo]()
Amazon S3 Parquet































































