Two-way sync
Changes in Amazon S3 or Apache Doris instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon S3 and Apache Doris in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Apache Doris 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 Apache Doris, or a result in Apache Doris 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 Databases, Tables, Unique Key Tables, Aggregate Key Tables in Apache Doris with Object versions, Prefixes (folders), Multipart uploads, Buckets 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.
Curated tables and query results from Apache Doris are written to Amazon S3 as files the rest of the business can open, keeping the shared copy current without a hand-run export.
Where the same dataset lives as a file in Amazon S3 and a table in Apache Doris, a change on either side propagates to the other, ending the drift between the file people read and the table people query.
The catalog of documents, owners, and folders in Amazon S3 appears as Databases, Tables, Unique Key Tables, Aggregate Key Tables in Apache Doris, so file metadata can be joined against the rest of your data and reported on.
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 | Apache Doris objects | How this pairing syncs | |
|---|---|---|---|
| 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. | Partitions Range or list partitions that bound incremental loads. | Object metadata is specific to Amazon S3 and Partitions to Apache Doris — 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. | Materialized Views Precomputed views readable for downstream syncs and BI. | Object tags is specific to Amazon S3 and Materialized Views to Apache Doris — 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. | Users and Roles Principals used to grant the sync connection scoped access. | Object versions is specific to Amazon S3 and Users and Roles to Apache Doris — 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. | Databases Logical containers that scope connections and grants. | Prefixes (folders) is specific to Amazon S3 and Databases to Apache Doris — 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. | Tables Columnar tables in one of Doris's table models, used as sync destinations. | Multipart uploads is specific to Amazon S3 and Tables to Apache Doris — 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. | Unique Key Tables Tables supporting primary-key upserts, the natural target for row-level syncs. | Buckets is specific to Amazon S3 and Unique Key Tables to Apache Doris — 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 Apache Doris as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Apache Doris for changes on an incremental schedule, reading only records changed since the previous pass. Polling on partition or timestamp columns for reads.
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–Apache Doris connection.
Changes in Amazon S3 or Apache Doris instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon S3 or Apache Doris 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 Apache Doris record.
Track your Amazon S3 ⇄ Apache Doris sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon S3 and Apache Doris.
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 Apache Doris 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 Apache Doris 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 Apache Doris: authenticate both systems, choose the objects to sync (such as Amazon S3's Object metadata and Object tags), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both Amazon S3 and Apache Doris. 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 Apache Doris: Polling on partition or timestamp columns for reads; ingestion into Doris is push-based via load jobs. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Apache Doris side: Databases, Tables, Unique Key Tables, Aggregate Key Tables, plus custom fields where Apache Doris exposes them. On the Amazon S3 side: Object versions, Prefixes (folders), Multipart uploads, Buckets. 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.
Common patterns for Amazon S3 and Apache Doris: Where Amazon S3 is the shared drive: publish results back as files; One dataset, kept consistent both ways; Where Amazon S3 holds the file inventory: make it queryable. Curated tables and query results from Apache Doris are written to Amazon S3 as files the rest of the business can open, keeping the shared copy current without a hand-run export.
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 Apache Doris.