Stream data from SQL Server Batch to Amazon S3 Parquet
Move data from SQL Server Batch to Amazon S3 Parquet in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.
- No credit card required
- 30-day free trial


- 200+Connectors
- 5500+Active users
- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate SQL Server Batch with Amazon S3 Parquet in 3 simple steps
- 1
Connect SQL Server Batch as your data source
Set up a source connector for SQL Server Batch in minutes. Estuary supports streaming (including CDC where available) and batch data capture through events, incremental syncs, or snapshots — without custom pipelines, agents, or manual configuration.
- 2
Configure Amazon S3 Parquet as your destination connector
Estuary supports intelligent schema handling, with schema inference and evolution tools that help align source and destination structures over time. It supports both batch and streaming data movement, reliably delivering data to Amazon S3 Parquet.
- 3
Deploy and Monitor Your End-to-End Data Pipeline
Launch your pipeline and monitor it from a single UI. Estuary guarantees exactly-once delivery, handles backfills and replays, and scales with your data — without engineering overhead.

SQL Server Batch connector details
The SQL Server Batch Query connector captures data from SQL Server by periodically executing queries and loading the results into Estuary collections. It is designed for scheduled batch ingestion rather than real-time CDC, making it useful when you need to capture database views, run custom SQL queries, use a read replica, or connect to a SQL Server instance that does not support CDC or Change Tracking.
- Scheduled query-based capture with configurable polling intervals
- Full-refresh and incremental capture using cursor-based queries
- Capture from SQL Server tables and database views
- Custom SQL queries for filtering, aggregations, or capturing specific subsets of data
- Read replica support for reducing load on the primary database
- Flexible cursor options, including update timestamps, creation timestamps, and auto-incrementing IDs
The connector supports self-hosted SQL Server as well as managed deployments such as Amazon RDS and Azure SQL Database.

Amazon S3 Parquet connector details
The Amazon S3 Parquet materialization connector writes delta updates from Estuary collections to an Amazon S3 bucket in Apache Parquet format, providing efficient, columnar storage optimized for analytics and downstream data lake use cases.
- Data format: Outputs batched delta updates as Parquet files for compact, query-ready storage
- Upload scheduling: Configure upload intervals and file size limits to control data batching frequency
- Flexible authentication: Supports both AWS Access Keys and IAM roles for secure access
- Schema-aware typing: Automatically maps Estuary collection field types to equivalent Parquet data types
- File versioning: Organizes files by path and version counters for easy traceability and reprocessing
- Scalable and compatible: Works with AWS S3 and S3-compatible APIs, such as MinIO or Wasabi
💡 Tip: Use this connector to build cost-efficient, analytics-ready data lakes by streaming Estuary data to S3 in Parquet format, ready for querying in Athena, Snowflake, or Databricks.
Estuary in action
See how to build end-to-end pipelines using no-code connectors in minutes. Estuary does the rest.
Spend 2-5x less
Estuary customers not only do 4x more. They also spend 2-5x less on ETL and ELT. Estuary's unique ability to mix and match streaming and batch loading has also helped customers save as much as 40% on data warehouse compute costs.

SQL Server Batch to Amazon S3 Parquet pricing estimate
Estimated monthly cost to move 800 GB from SQL Server Batch to Amazon S3 Parquet is approximately $1,000.
Data moved
Choose how much data you want to move from SQL Server Batch to Amazon S3 Parquet each month.
GB
Choose number of sources and destinations.
Why pay more?
Move the same data for a fraction of the cost.



What customers are saying
Getting started with Estuary
Free account
Getting started with Estuary is simple. Sign up for a free account.
Sign upDocs
Make sure you read through the documentation, especially the get started section.
Learn moreCommunity
Join the Slack community for the easiest way to get support while getting started.
Join Slack CommunityEstuary 101
Watch the Estuary 101 webinar for a guided introduction to using Estuary.
Watch

Frequently Asked Questions
Is this integration suitable for production workloads?
Yes. Estuary pipelines are designed for production use, with exactly-once delivery semantics, automated backfills, and continuous operation at scale.
Can I control where my data runs and is processed?
Yes. Estuary offers multiple deployment options, including fully managed SaaS, private deployments, and bring-your-own-cloud (BYOC). This allows teams to control where their data plane runs and meet security, compliance, and networking requirements. Learn more about Estuary's security and deployment options.
Can I build this SQL Server Batch to Amazon S3 Parquet integration manually?
Yes, it's possible to build a manual pipeline using custom scripts, scheduled jobs, or open-source tools. However, manual approaches typically require ongoing maintenance, custom error handling, schema management, and operational overhead. Estuary simplifies this by providing a managed pipeline with built-in reliability, scaling, and monitoring.
Related integrations with SQL Server Batch
DataOps made simple
Add advanced capabilities like schema inference and evolution with a few clicks. Or automate your data pipeline and integrate into your existing DataOps using Estuary's rich CLI.


































