Two-way sync
Changes in Amazon S3 or Rockset instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon S3 and Rockset in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Rockset 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 Rockset, or a result in Rockset 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 Workspaces, Query Lambdas, Aliases, Integrations in Rockset with Object tags, Object versions, Prefixes (folders), Multipart uploads 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.
The catalog of documents, owners, and folders in Amazon S3 appears as Workspaces, Query Lambdas, Aliases, Integrations in Rockset, so file metadata can be joined against the rest of your data and reported on.
Classifications, scores, or status derived in Rockset are written back onto the matching Object tags, Object versions, Prefixes (folders), Multipart uploads 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 Workspaces, Query Lambdas, Aliases, Integrations in Rockset as they land, so analysts query current data instead of waiting on the next scheduled load.
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 | Rockset objects | How this pairing syncs | |
|---|---|---|---|
| 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. | Virtual Instances Isolated compute units that separate ingest from query workloads. | Multipart uploads is specific to Amazon S3 and Virtual Instances to Rockset — 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. | Collections Schemaless document containers that ingested and synced records land in. | Buckets is specific to Amazon S3 and Collections to Rockset — 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. | Documents JSON records addressable by _id, written via the Write API in sync pipelines. | Objects is specific to Amazon S3 and Documents to Rockset — 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. | Workspaces Namespaces that group collections and query lambdas per team or environment. | Object metadata is specific to Amazon S3 and Workspaces to Rockset — 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. | Query Lambdas Named, parameterized SQL queries invoked over REST to read synced data. | Object tags is specific to Amazon S3 and Query Lambdas to Rockset — 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. | Aliases Stable names that point at collections, used to swap datasets without changing queries. | Object versions is specific to Amazon S3 and Aliases to Rockset — 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 Rockset as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Rockset for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL queries on timestamp fields.
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–Rockset connection.
Changes in Amazon S3 or Rockset instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon S3 or Rockset 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 Rockset record.
Track your Amazon S3 ⇄ Rockset sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon S3 and Rockset.
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 Rockset 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 Rockset 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 Rockset: authenticate both systems, choose the objects to sync (such as Amazon S3's Multipart uploads and Buckets), 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 Rockset connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Amazon S3–Rockset integration in-house.
Yes — Stacksync ships production-grade connectors for both Amazon S3 and Rockset. 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 Rockset: Polling via SQL queries on timestamp fields; ingestion-side change capture is handled by Rockset's managed source connectors. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Rockset side: Workspaces, Query Lambdas, Aliases, Integrations, plus custom fields where Rockset exposes them. On the Amazon S3 side: Object tags, Object versions, Prefixes (folders), Multipart uploads. 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.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 493 integrations available for Amazon S3 and Rockset.