Skip to content
Storage ⇄ Data warehouse

Amazon S3 to Apache Kylin integration — real-time data sync

Keep Amazon S3 and Apache Kylin 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 Apache Kylin

Flow Apache Kylin data into Amazon S3 in real time — no exports, no schedulers, no custom scripts.

Apache Kylin is a read-only source: Stacksync reads its data in real time and delivers it into Amazon S3, so Amazon S3 always reflects the current state of Apache Kylin — without exports, scripts, or schedulers.

Apache Kylin 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 Kylin, or a result in Apache Kylin 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.

Common use cases

  • 01 Read pre-aggregated metrics from Kylin and sync them into CRM fields or planning spreadsheets on a schedule.
  • 02 Expose Kylin query results to operational dashboards without granting access to the underlying Hadoop data.
  • 03 Two-way sync Object tags with a database so retention or classification labels set in an internal app write back onto S3 objects via the tagging API without rewriting the files.
  • 04 Mirror Objects under a given Bucket and prefix into another bucket, region, or a warehouse external stage for backup or downstream processing.

Common sync patterns

Where Apache Kylin computes the labels: push them onto the files

Classifications, scores, or status derived in Apache Kylin 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.

Where Amazon S3 receives the raw files: land them as query-ready rows

Files and exports that arrive in Amazon S3 are parsed into Build Jobs, Projects, Models, Cubes / Indexes in Apache Kylin as they land, so analysts query current data instead of waiting on the next scheduled load.

Where Amazon S3 is the shared drive: publish results back as files

Curated tables and query results from Apache Kylin are written to Amazon S3 as files the rest of the business can open, keeping the shared copy current without a hand-run export.

What you can sync between Amazon S3 and Apache Kylin

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 Kylin 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. Segments Time-ranged build units that partition pre-computed data. Object versions is specific to Amazon S3 and Segments to Apache Kylin — 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. Build Jobs Batch jobs that compute or refresh segments, monitored via the REST API. Prefixes (folders) is specific to Amazon S3 and Build Jobs to Apache Kylin — 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. Projects Top-level workspaces that group models, tables, and jobs. Multipart uploads is specific to Amazon S3 and Projects to Apache Kylin — 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. Models Star-schema definitions over source tables that determine what can be queried. Buckets is specific to Amazon S3 and Models to Apache Kylin — 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. Cubes / Indexes Pre-computed aggregate structures that answer queries at low latency. Objects is specific to Amazon S3 and Cubes / Indexes to Apache Kylin — 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. Source Tables Hive or other upstream tables that builds read from. Object metadata is specific to Amazon S3 and Source Tables to Apache Kylin — each maps to any object or custom field on the other side.

How changes propagate between Amazon S3 and Apache Kylin

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 Apache Kylin 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.

DeliveryApache Kylin does not accept inbound record writes, so this direction carries requests rather than records: Apache Kylin's output flows back as field updates on the originating Amazon S3 records.

Apache Kylin Amazon S3 Interval-based propagation

DetectionStacksync polls Apache Kylin for changes on an incremental schedule, reading only records changed since the previous pass. Data freshness follows segment build and refresh jobs, so integrations poll query results.

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.
  • Apache Kylin: No fixed API quotas; query capacity depends on the deployment and pre-computed index coverage.
What ships with Amazon S3 ⇄ Apache Kylin

Connect Amazon S3 and Apache Kylin for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–Apache Kylin connection.

Real-time

Real-time sync

Changes in Amazon S3 or Apache Kylin instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon S3 or Apache Kylin 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 Apache Kylin record.

Observability

Monitoring

Track your Amazon S3 ⇄ Apache Kylin 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 Apache Kylin.

How the Amazon S3 and Apache Kylin 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.

Apache Kylin

Integration surface
SQL over JDBC/ODBC plus a REST API for queries and administration
Authentication
Username/password (HTTP basic authentication on the REST API)
Change detection
Not applicable for row-level capture; data freshness follows segment build and refresh jobs, so integrations poll query results
Capabilities
read
Rate limits
No fixed API quotas; query capacity depends on the deployment and pre-computed index coverage
How it works

How to connect Amazon S3 to Apache Kylin — 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.

  1. 01

    Connect your apps

    Authenticate Amazon S3 and Apache Kylin with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Amazon S3 connected
    Apache Kylin connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon S3 and Apache Kylin 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Amazon S3 ⇄ Apache Kylin
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Amazon S3 Apache Kylin
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Amazon S3 and Apache Kylin integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 383 integrations available for Amazon S3 and Apache Kylin.

Popular · 7 of 383
All Amazon S3 integrations All Apache Kylin integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own