Real-time
Two-way sync
Changes in Amazon S3 or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Storage ⇄ Database
Amazon S3 to TimescaleDB integration — real-time, two-way sync
Keep Amazon S3 and TimescaleDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Amazon S3 and TimescaleDB
Keep TimescaleDB and Amazon S3 in step: a row in TimescaleDB 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 TimescaleDB 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 Views, Schemas, Hypertables, Chunks in TimescaleDB 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 Sync product or IoT telemetry stored in TimescaleDB into a CRM so account teams see usage metrics next to the customer record.
- 02 Replicate subscription and billing events from operational Postgres tables into Timescale hypertables for time-series analysis.
- 03 Mirror Objects under a given Bucket and prefix into another bucket, region, or a warehouse external stage for backup or downstream processing.
- 04 Trigger a database or ERP record update the moment an S3 Event Notification fires an object-created event, for example when a partner drops an EDI or invoice file into an inbound prefix.
Common sync patterns
A queryable index of the file store
Every file or object in Amazon S3 shows up as a row in TimescaleDB, with its name, folder or key, size, type, and modified date as columns, so the contents of the store can be listed, filtered, and joined like any other table.
File metadata kept in step
Tags, custom properties, owner, or status columns edited on a row in TimescaleDB write back to the matching file's metadata in Amazon S3, and metadata changed in Amazon S3 updates the row, so the two never disagree about a file.
Records that point at documents
Where a record in TimescaleDB 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.
What you can sync between Amazon S3 and TimescaleDB
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 | TimescaleDB objects | How this pairing syncs | |
|---|---|---|---|
| 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. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. | Object versions is specific to Amazon S3 and Regular PostgreSQL Tables to TimescaleDB — 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. | Views Standard SQL views used to shape or filter data for consumers. | Prefixes (folders) is specific to Amazon S3 and Views to TimescaleDB — each maps to any object or custom field on the other side. | |
| Multipart uploads In-progress large-object uploads assembled from parts; objects above ~100 MB (required above 5 GB) are written this way, and incomplete uploads persist until completed or aborted. | Schemas Postgres namespaces used to separate synced datasets by team or environment. | Multipart uploads is specific to Amazon S3 and Schemas to TimescaleDB — each maps to any object or custom field on the other side. | |
| Buckets Top-level, region-scoped containers that hold objects; enumerated to discover the namespaces and prefixes a sync should cover. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | Buckets is specific to Amazon S3 and Hypertables to TimescaleDB — 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. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. | Objects is specific to Amazon S3 and Chunks to TimescaleDB — 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. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | Object metadata is specific to Amazon S3 and Continuous Aggregates to TimescaleDB — each maps to any object or custom field on the other side. |
How changes propagate between Amazon S3 and TimescaleDB
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 TimescaleDB 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 TimescaleDB as a row-level write, with types converted between the two schemas.
TimescaleDB Amazon S3 Sub-second propagation
DetectionChanges in TimescaleDB are captured at the source via change data capture — no polling loop against its API. Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must.
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.
- TimescaleDB: No API rate limits; throughput is bounded by database resources and connection limits.
What ships with Amazon S3 ⇄ TimescaleDB
Connect Amazon S3 and TimescaleDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–TimescaleDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Amazon S3 or TimescaleDB 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 TimescaleDB record.
Observability
Monitoring
Track your Amazon S3 ⇄ TimescaleDB 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 TimescaleDB.
How the Amazon S3 and TimescaleDB 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.
TimescaleDB
- Integration surface
- SQL wire protocol (PostgreSQL)
- Authentication
- Database credentials
- Change detection
- Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput is bounded by database resources and connection limits.
How it works
How to connect Amazon S3 to TimescaleDB — 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.
- 01
Connect your apps
Authenticate Amazon S3 and TimescaleDB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Amazon S3
connected
TimescaleDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Amazon S3 and TimescaleDB 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.
objects · Amazon S3 ⇄ TimescaleDBCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Amazon S3 TimescaleDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Amazon S3 and TimescaleDB integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Amazon S3 and TimescaleDB: authenticate both systems, choose the objects to sync (such as Amazon S3's Object versions and Prefixes (folders)), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
-
Common patterns for Amazon S3 and TimescaleDB: A queryable index of the file store; File metadata kept in step; Records that point at documents. Every file or object in Amazon S3 shows up as a row in TimescaleDB, with its name, folder or key, size, type, and modified date as columns, so the contents of the store can be listed, filtered, and joined like any other table.
-
Amazon S3: 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. TimescaleDB: SQL wire protocol (PostgreSQL). Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
-
TimescaleDB: Native compression converts older chunks to a columnar layout while keeping them queryable with the same SQL. Amazon S3: User-defined metadata (x-amz-meta-*) is fixed when an object is written and changing it requires copying the object over itself; only object tags can be updated in place via the tagging API (max 10 tags per object). Stacksync's field mapping accounts for these differences between Amazon S3 and TimescaleDB without custom code.
-
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Amazon S3 and TimescaleDB records are not retained after a sync operation.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 420 integrations available for Amazon S3 and TimescaleDB.
Popular · 7 of 420
-
Amazon S3 ⇄ MySQL -
Amazon S3 ⇄ MariaDB -
Amazon S3 ⇄ SQL Server -
Amazon S3 ⇄ Postgres Heroku -
TimescaleDB ⇄ Sharepoint -
TimescaleDB ⇄ Egnyte -
TimescaleDB ⇄ Box
No integrations match .
