Two-way sync
Changes in Amazon S3 or YugabyteDB instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon S3 and YugabyteDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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 YugabyteDB 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 Materialized Views, Schemas, Sequences, CDC Streams in YugabyteDB with Buckets, Objects, Object metadata, Object tags 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.
Tags, custom properties, owner, or status columns edited on a row in YugabyteDB 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.
Where a record in YugabyteDB 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.
Files that arrive in a folder or bucket in Amazon S3 become rows in YugabyteDB as they land, so a database-driven process can pick them up without polling the storage system's API.
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 | YugabyteDB objects | How this pairing syncs | |
|---|---|---|---|
| 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. | Schemas Postgres-style namespaces in YSQL used to organize synced data. | Objects is specific to Amazon S3 and Schemas to YugabyteDB — 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. | Sequences ID generation objects relevant when syncing writes into YSQL tables. | Object metadata is specific to Amazon S3 and Sequences to YugabyteDB — 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. | CDC Streams Change streams over the storage-layer WAL consumed through logical replication or Debezium-compatible connectors. | Object tags is specific to Amazon S3 and CDC Streams to YugabyteDB — 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. | Databases and Keyspaces Top-level containers for the YSQL (Postgres-style) and YCQL (Cassandra-style) APIs respectively. | Object versions is specific to Amazon S3 and Databases and Keyspaces to YugabyteDB — 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. | Tables Distributed SQL tables split into tablets; the primary read and write targets. | Prefixes (folders) is specific to Amazon S3 and Tables to YugabyteDB — 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. | Indexes Global secondary indexes maintained transactionally alongside table writes. | Multipart uploads is specific to Amazon S3 and Indexes to YugabyteDB — 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 YugabyteDB as a row-level write, with types converted between the two schemas.
DetectionChanges in YugabyteDB are captured at the source via change data capture — no polling loop against its API. Native CDC from the write-ahead log via PostgreSQL logical replication or Debezium-compatible connectors.
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–YugabyteDB connection.
Changes in Amazon S3 or YugabyteDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon S3 or YugabyteDB 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 YugabyteDB record.
Track your Amazon S3 ⇄ YugabyteDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon S3 and YugabyteDB.
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 YugabyteDB 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 YugabyteDB 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 YugabyteDB: authenticate both systems, choose the objects to sync (such as Amazon S3's Objects and Object metadata), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for Amazon S3 and YugabyteDB: File metadata kept in step; Records that point at documents; A landing zone for incoming files. Tags, custom properties, owner, or status columns edited on a row in YugabyteDB 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.
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. YugabyteDB: SQL wire protocol (PostgreSQL-compatible YSQL) plus a Cassandra-compatible YCQL API. Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
YugabyteDB: A second, Cassandra-compatible API (YCQL) is available alongside YSQL on the same cluster. Amazon S3: S3 provides strong read-after-write consistency for all operations, but it has no built-in change feed — near-real-time detection depends on S3 Event Notifications or EventBridge being configured on the bucket. Stacksync's field mapping accounts for these differences between Amazon S3 and YugabyteDB 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 YugabyteDB records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Amazon S3 and YugabyteDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Amazon S3–YugabyteDB integration in-house.
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 420 integrations available for Amazon S3 and YugabyteDB.