Real-time
Two-way sync
Changes in Amazon Aurora or OpenSearch instantly reflect in both systems. No stale data, no manual imports.
Database
Amazon Aurora to OpenSearch integration — real-time, two-way sync
Keep Amazon Aurora and OpenSearch 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 Aurora and OpenSearch
Keep Amazon Aurora and OpenSearch synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between Amazon Aurora and OpenSearch continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- 01 Consolidate several Aurora clusters into one reporting database.
- 02 Write enriched or scored records from analytics pipelines back into the Aurora tables that power an application.
- 03 Index support tickets and activity logs from SaaS tools for operational dashboards.
- 04 Backfill or rebuild indexes from a database after mapping changes without hand-written ETL.
Common sync patterns
Migration with zero-downtime cutover
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
What you can sync between Amazon Aurora and OpenSearch
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 Aurora objects | OpenSearch objects | How this pairing syncs | |
|---|---|---|---|
| Databases Logical databases within a cluster that scope a sync connection. | Data streams Append-oriented time-series storage for logs and events pushed from source systems | Databases is specific to Amazon Aurora and Data streams to OpenSearch — each maps to any object or custom field on the other side. | |
| Schemas Namespaces (PostgreSQL) or database-level grouping (MySQL) used in table selection. | Snapshots Backup artifacts, relevant when reseeding an index from a repository | Schemas is specific to Amazon Aurora and Snapshots to OpenSearch — each maps to any object or custom field on the other side. | |
| Tables Relational tables synced bi-directionally at row level. | Indexes The core container; synced records land in indexes with defined mappings | Tables is specific to Amazon Aurora and Indexes to OpenSearch — each maps to any object or custom field on the other side. | |
| Views Read-only query-backed sources for downstream syncs. | Documents JSON records written via the index and bulk APIs and read via search queries | Views is specific to Amazon Aurora and Documents to OpenSearch — each maps to any object or custom field on the other side. | |
| Materialized Views Precomputed result sets (PostgreSQL-compatible clusters) readable as sources. | Index aliases Stable names over rotating indexes, used for zero-downtime reindex during backfills | Materialized Views is specific to Amazon Aurora and Index aliases to OpenSearch — each maps to any object or custom field on the other side. | |
| Columns and Data Types Standard MySQL or PostgreSQL types mapped during field mapping. | Index templates Mapping and settings presets applied to new indexes a sync creates | Columns and Data Types is specific to Amazon Aurora and Index templates to OpenSearch — each maps to any object or custom field on the other side. |
How changes propagate between Amazon Aurora and OpenSearch
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 Aurora OpenSearch Sub-second propagation
DetectionChanges in Amazon Aurora are captured at the source via change data capture — no polling loop against its API. Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters.
DeliveryEach detected change is written to OpenSearch through its API, with automatic retries and rate-limit backoff.
OpenSearch Amazon Aurora Interval-based propagation
DetectionStacksync polls OpenSearch for changes on an incremental schedule, reading only records changed since the previous pass. No native change feed.
DeliveryEach detected change is applied to Amazon Aurora as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Amazon Aurora: No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits.
- OpenSearch: Throughput bounded by cluster sizing rather than fixed API quotas.
What ships with Amazon Aurora ⇄ OpenSearch
Connect Amazon Aurora and OpenSearch for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Aurora–OpenSearch connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Amazon Aurora or OpenSearch 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 Aurora or OpenSearch record.
Observability
Monitoring
Track your Amazon Aurora ⇄ OpenSearch sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Amazon Aurora and OpenSearch.
How the Amazon Aurora and OpenSearch connectors work
Amazon Aurora
- Integration surface
- MySQL or PostgreSQL wire protocol (SQL); optional RDS Data API over HTTPS
- Authentication
- Database credentials or IAM database authentication
- Change detection
- Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters; polling as a fallback
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits
OpenSearch
- Integration surface
- REST API over HTTP(S) with JSON payloads
- Authentication
- basic authentication with the security plugin, or AWS IAM request signing on Amazon OpenSearch Service
- Change detection
- no native change feed; reads rely on queries with scroll or point-in-time polling
- Capabilities
- read · write
- Rate limits
- throughput bounded by cluster sizing rather than fixed API quotas
How it works
How to connect Amazon Aurora to OpenSearch — 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.
- 01
Connect your apps
Authenticate Amazon Aurora and OpenSearch with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Amazon Aurora
connected
OpenSearch
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Amazon Aurora and OpenSearch 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.
objects · Amazon Aurora ⇄ OpenSearchCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Amazon Aurora OpenSearchCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Amazon Aurora and OpenSearch integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Amazon Aurora and OpenSearch: authenticate both systems, choose the objects to sync (such as Amazon Aurora's Databases and Schemas), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Amazon Aurora: MySQL or PostgreSQL wire protocol (SQL); optional RDS Data API over HTTPS. Authentication: Database credentials or IAM database authentication. OpenSearch: REST API over HTTP(S) with JSON payloads. Authentication: Basic authentication with the security plugin, or AWS IAM request signing on Amazon OpenSearch Service. Stacksync manages authentication, retries, and rate limits on both sides.
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Amazon Aurora: Change data capture uses the native engine mechanisms: MySQL binary log on Aurora MySQL and logical replication on Aurora PostgreSQL. OpenSearch: The bulk API accepts many index, update, and delete operations per request, which is how large indexes are kept current. Stacksync's field mapping accounts for these differences between Amazon Aurora and OpenSearch without custom code.
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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 Aurora and OpenSearch records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Amazon Aurora and OpenSearch connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Amazon Aurora–OpenSearch integration in-house.
-
Yes — Stacksync ships production-grade connectors for both Amazon Aurora and OpenSearch. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 352 integrations available for Amazon Aurora and OpenSearch.
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