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Storage ⇄ Database

Amazon S3 to SQL Server integration — real-time, two-way sync

Keep Amazon S3 and SQL Server in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Why teams connect Amazon S3 and SQL Server

Keep SQL Server and Amazon S3 in step: a row in SQL Server for every file in Amazon S3, with names, paths, metadata, and status staying consistent in real time, in both directions.

A database holds structured records; a storage system holds the files those records depend on, such as contracts, images, exports, uploads, and documents. The two describe the same things from opposite sides: a row in SQL Server says a file exists and carries its name, location, and status, while Amazon S3 holds the bytes. Linked only by a hand-kept path or a one-off script, the two drift the moment a file is renamed, moved, or deleted and the record still points at where it used to be.

Stacksync syncs Stored Procedures, Databases, Schemas, Tables in SQL Server with Object tags, Object versions, Prefixes (folders), Multipart uploads in Amazon S3 bi-directionally and in real time. File attributes, including name, path or object key, size, type, modified time, owner, and tags or custom properties, map field by field to columns on the matching row, and a change on either side shows up on the other within seconds. New files appear as rows, metadata edits travel in the direction you choose, and deletes stay consistent, with conflict rules you set in place of nightly reconciliation scripts.

Common use cases

  • 01 Feed a cloud warehouse from SQL Server continuously using native CDC instead of SSIS batch jobs
  • 02 Consolidate branch or plant databases into a single operational SQL Server hub
  • 03 Two-way sync Object tags with a database so retention or classification labels set in an internal app write back onto S3 objects via the tagging API without rewriting the files.
  • 04 Mirror Objects under a given Bucket and prefix into another bucket, region, or a warehouse external stage for backup or downstream processing.

Common sync patterns

Records that point at documents

Where a record in SQL Server references a file in Amazon S3, such as a contract, an image, an export, or an upload, the reference, path, and status stay consistent as files are renamed, moved, or replaced, so stored links keep resolving.

A landing zone for incoming files

Files that arrive in a folder or bucket in Amazon S3 become rows in SQL Server as they land, so a database-driven process can pick them up without polling the storage system's API.

Continuous archival to file storage

Rows from SQL Server are written out to Amazon S3 as files on a schedule or as they change, giving a durable, low-cost copy for backup, compliance, or a data lake, without a custom export job to maintain.

What you can sync between Amazon S3 and SQL Server

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Amazon S3 objects SQL Server objects How this pairing syncs
Buckets Top-level, region-scoped containers that hold objects; enumerated to discover the namespaces and prefixes a sync should cover. Tables The primary sync target; rows map to records in connected systems. Buckets is specific to Amazon S3 and Tables to SQL Server — each maps to any object or custom field on the other side.
Objects Files stored under a key; content is read with GET and written with PUT, and each object's key/size/ETag/LastModified is the unit indexed into a database. Views Read-side projections used as outbound sync sources. Objects is specific to Amazon S3 and Views to SQL Server — each maps to any object or custom field on the other side.
Object metadata System metadata (Content-Type, size, ETag, LastModified) plus user-defined x-amz-meta-* headers; user metadata is fixed at write time and only changeable by rewriting the object. Columns Field-level mapping targets with T-SQL types. Object metadata is specific to Amazon S3 and Columns to SQL Server — each maps to any object or custom field on the other side.
Object tags Up to 10 key-value tags per object, mutable in place via the tagging API independent of content, so classification and retention labels sync two-way without rewriting files. Primary and Unique Keys Match keys for idempotent upserts and conflict handling. Object tags is specific to Amazon S3 and Primary and Unique Keys to SQL Server — each maps to any object or custom field on the other side.
Object versions When bucket versioning is enabled every write creates a new version ID; prior versions and delete markers are readable for history and audit syncs. CDC Change Tables System-populated tables holding captured inserts, updates, and deletes for consumers. Object versions is specific to Amazon S3 and CDC Change Tables to SQL Server — each maps to any object or custom field on the other side.
Prefixes (folders) Logical path segments in object keys used to scope a sync and to parallelize throughput, since S3 rate limits partition by prefix. Stored Procedures T-SQL logic that can validate or post-process synced rows. Prefixes (folders) is specific to Amazon S3 and Stored Procedures to SQL Server — each maps to any object or custom field on the other side.

How changes propagate between Amazon S3 and SQL Server

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Amazon S3 SQL Server Sub-second propagation

DetectionAmazon S3 notifies Stacksync of record changes through webhook events. S3 Event Notifications push object-created, object-removed, and object-tagging events to SNS, SQS, Lambda, or EventBridge.

DeliveryEach detected change is applied to SQL Server as a row-level write, with types converted between the two schemas.

SQL Server Amazon S3 Sub-second propagation

DetectionChanges in SQL Server are captured at the source via change data capture — no polling loop against its API. SQL Server Native Change Data Capture (CDC).

DeliveryEach detected change is written to Amazon S3 through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Amazon S3: S3 sustains at least 3,500 PUT/COPY/POST/DELETE and 5,500 GET/HEAD requests per second per partitioned prefix and scales higher automatically; bursts can return HTTP 503 SlowDown while it repartitions.
  • SQL Server: No API rate limits; throughput depends on instance resources, licensing tier, and connection limits.
What ships with Amazon S3 ⇄ SQL Server

Connect Amazon S3 and SQL Server for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–SQL Server connection.

Real-time

Two-way sync

Changes in Amazon S3 or SQL Server instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon S3 or SQL Server data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Amazon S3 or SQL Server record.

Observability

Monitoring

Track your Amazon S3 ⇄ SQL Server sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon S3 and SQL Server.

How the Amazon S3 and SQL Server connectors work

Amazon S3

Integration surface
S3 REST API (also via AWS SDKs and the S3-compatible endpoint)
Authentication
AWS IAM credentials — an access key ID and secret access key signed with AWS Signature Version 4; supports temporary STS credentials and cross-account IAM roles
Change detection
S3 Event Notifications push object-created, object-removed, and object-tagging events to SNS, SQS, Lambda, or EventBridge; there is no modified-since query, so polling relies on each object's LastModified from ListObjectsV2
Capabilities
read · write · webhooks
Rate limits
S3 sustains at least 3,500 PUT/COPY/POST/DELETE and 5,500 GET/HEAD requests per second per partitioned prefix and scales higher automatically; bursts can return HTTP 503 SlowDown while it repartitions.

SQL Server

Integration surface
SQL over the TDS wire protocol (Tabular Data Stream), via ODBC/JDBC/ADO.NET drivers
Authentication
Database credentials entered as a connection string or as parameters (host/user/password) in the Create New Sync page
Change detection
SQL Server Native Change Data Capture (CDC); a DBA runs a one-time setup script with sysadmin privileges to enable CDC and create Stacksync wrapper procedures
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput depends on instance resources, licensing tier, and connection limits
SQL Server setup guide
How it works

How to connect Amazon S3 to SQL Server — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Amazon S3 and SQL Server with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Amazon S3 connected
    SQL Server connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon S3 and SQL Server objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Amazon S3 ⇄ SQL Server
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Amazon S3 SQL Server
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon S3 and SQL Server integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 530 integrations available for Amazon S3 and SQL Server.

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