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Storage ⇄ Database

Amazon S3 to Elasticsearch integration — real-time, two-way sync

Keep Amazon S3 and Elasticsearch in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Amazon S3 and Elasticsearch

Keep Elasticsearch and Amazon S3 in step: a row in Elasticsearch for every file in Amazon S3, with names, paths, metadata, and status staying consistent in real time, in both directions.

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 Elasticsearch 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 Aliases, Data streams, Ingest pipelines, Index templates in Elasticsearch with Object versions, Prefixes (folders), Multipart uploads, Buckets 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.

Common use cases

  • 01 Feed enriched customer records into an index used for vector or hybrid search in AI applications.
  • 02 Sync CRM accounts and contacts into an Elasticsearch index to power internal search across customer records.
  • 03 Reconcile Object versions and delete markers into an audit table so teams track when files under a compliance prefix were added, replaced, or removed.
  • 04 Index every new Object's key, size, LastModified, and user metadata into a Postgres catalog table so applications query S3 contents in SQL instead of paging ListObjectsV2.

Common sync patterns

Records that point at documents

Where a record in Elasticsearch 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.

A landing zone for incoming files

Files that arrive in a folder or bucket in Amazon S3 become rows in Elasticsearch as they land, so a database-driven process can pick them up without polling the storage system's API.

Continuous archival to file storage

Rows from Elasticsearch are written out to Amazon S3 as files on a schedule or as they change, giving a durable, low-cost copy for backup, compliance, or a data lake, without a custom export job to maintain.

What you can sync between Amazon S3 and Elasticsearch

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 Elasticsearch 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. Data streams Append-only targets for time-series or event data pushed from source systems. Objects is specific to Amazon S3 and Data streams to Elasticsearch — 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. Ingest pipelines Server-side transforms applied to documents as a sync writes them. Object metadata is specific to Amazon S3 and Ingest pipelines to Elasticsearch — 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. Index templates Reusable settings and mappings applied automatically to new indices a sync creates. Object tags is specific to Amazon S3 and Index templates to Elasticsearch — 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. Indices Target containers for synced records; each holds a table-like collection of JSON documents. Object versions is specific to Amazon S3 and Indices to Elasticsearch — 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. Documents The unit of sync; JSON records created, updated, and deleted by _id. Prefixes (folders) is specific to Amazon S3 and Documents to Elasticsearch — 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. Index mappings Field type definitions that determine how synced fields are indexed and queried. Multipart uploads is specific to Amazon S3 and Index mappings to Elasticsearch — each maps to any object or custom field on the other side.

How changes propagate between Amazon S3 and Elasticsearch

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 Elasticsearch 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.

DeliveryEach detected change is written to Elasticsearch through its API, with automatic retries and rate-limit backoff.

Elasticsearch Amazon S3 Interval-based propagation

DetectionStacksync polls Elasticsearch for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or sequence fields.

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.
  • Elasticsearch: No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity.
What ships with Amazon S3 ⇄ Elasticsearch

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon S3 or Elasticsearch 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 Elasticsearch record.

Observability

Monitoring

Track your Amazon S3 ⇄ Elasticsearch 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 Elasticsearch.

How the Amazon S3 and Elasticsearch 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.

Elasticsearch

Integration surface
REST API (JSON over HTTP)
Authentication
API keys or basic authentication; Elastic Cloud also issues service account tokens
Change detection
Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks
Capabilities
read · write
Rate limits
No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity
How it works

How to connect Amazon S3 to Elasticsearch — 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 Elasticsearch 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
    Elasticsearch connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon S3 and Elasticsearch 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 ⇄ Elasticsearch
    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 Elasticsearch
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon S3 and Elasticsearch 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.

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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 511 integrations available for Amazon S3 and Elasticsearch.

Popular · 7 of 511
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