Two-way sync
Changes in Amazon S3 or Starburst Enterprise instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon S3 and Starburst Enterprise in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Starburst Enterprise keeps the tables and query results a business reports on; Amazon S3 keeps the raw files, documents, and objects that the same business produces and shares. The two overlap wherever a dataset lives as both — a file dropped in Amazon S3 that has to become rows in Starburst Enterprise, or a result in Starburst Enterprise that people downstream need back as a file in Amazon S3. When that overlap is bridged by manual export and import or an overnight job, one side spends the day working from a stale copy.
Stacksync syncs Columns, Catalogs, Schemas, Tables in Starburst Enterprise with Object metadata, Object tags, Object versions, Prefixes (folders) in Amazon S3 field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set.
Classifications, scores, or status derived in Starburst Enterprise are written back onto the matching Object metadata, Object tags, Object versions, Prefixes (folders) in Amazon S3 as metadata or tags, so the file store reflects what analytics decided.
Files and exports that arrive in Amazon S3 are parsed into Columns, Catalogs, Schemas, Tables in Starburst Enterprise as they land, so analysts query current data instead of waiting on the next scheduled load.
Curated tables and query results from Starburst Enterprise are written to Amazon S3 as files the rest of the business can open, keeping the shared copy current without a hand-run export.
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 | Starburst Enterprise 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. | Tables Queryable relations; writes pass through to sources whose connectors support them. | Object versions is specific to Amazon S3 and Tables to Starburst Enterprise — 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 Engine-level SQL views used to shape federated data before syncing it out. | Prefixes (folders) is specific to Amazon S3 and Views to Starburst Enterprise — 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. | Materialized views Precomputed results that make repeated sync reads cheaper. | Multipart uploads is specific to Amazon S3 and Materialized views to Starburst Enterprise — 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. | Columns Typed per the Trino type system, mapped from each source's native types. | Buckets is specific to Amazon S3 and Columns to Starburst Enterprise — 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. | Catalogs Each catalog maps to a connector (Iceberg, Hive, PostgreSQL, and others) exposing an external source. | Objects is specific to Amazon S3 and Catalogs to Starburst Enterprise — 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. | Schemas Namespaces within a catalog, mirroring the underlying source's databases or schemas. | Object metadata is specific to Amazon S3 and Schemas to Starburst Enterprise — each maps to any object or custom field on the other side. |
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.
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 Starburst Enterprise as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Starburst Enterprise for changes on an incremental schedule, reading only records changed since the previous pass. Query-based polling.
DeliveryEach detected change is written to Amazon S3 through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–Starburst Enterprise connection.
Changes in Amazon S3 or Starburst Enterprise instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon S3 or Starburst Enterprise data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Amazon S3 or Starburst Enterprise record.
Track your Amazon S3 ⇄ Starburst Enterprise sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon S3 and Starburst Enterprise.
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.
Authenticate Amazon S3 and Starburst Enterprise with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Amazon S3 and Starburst Enterprise 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Amazon S3 and Starburst Enterprise: 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.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Amazon S3 and Starburst Enterprise connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Amazon S3–Starburst Enterprise integration in-house.
Yes — Stacksync ships production-grade connectors for both Amazon S3 and Starburst Enterprise. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Amazon S3: 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. On Starburst Enterprise: Query-based polling; Starburst is a query engine and exposes no change log of its own. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Starburst Enterprise side: Columns, Catalogs, Schemas, Tables, plus custom fields where Starburst Enterprise exposes them. On the Amazon S3 side: Object metadata, Object tags, Object versions, Prefixes (folders). Stacksync auto-detects both schemas and converts types between the two systems.
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.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
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Every pair below is a real-time, two-way sync. Search all 427 integrations available for Amazon S3 and Starburst Enterprise.