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AWS Aurora PostgreSQL to MarkLogic integration — real-time, two-way sync

Keep AWS Aurora PostgreSQL and MarkLogic 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

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Why teams connect AWS Aurora PostgreSQL and MarkLogic

Keep AWS Aurora PostgreSQL and MarkLogic 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 AWS Aurora PostgreSQL and MarkLogic 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 Feed operational dashboards from a read replica while the writer handles sync traffic.
  • 02 Expose ERP records such as customers, orders, and invoices as Postgres tables the engineering team can query and update with plain SQL.
  • 03 Feed harmonized entities into search and analytics applications as documents change.
  • 04 Sync curated master data from a MarkLogic data hub into operational CRMs and ERPs.

Common sync patterns

Cross-engine sync

Keep the same dataset live in both AWS Aurora PostgreSQL and MarkLogic, so each workload runs on the engine that suits it.

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.

What you can sync between AWS Aurora PostgreSQL and MarkLogic

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.

AWS Aurora PostgreSQL objects MarkLogic objects How this pairing syncs
Rows Inserted, updated, and deleted in both directions during bi-directional syncs. Semantic Triples RDF data stored alongside documents, queryable with SPARQL for linked-data syncs. Rows is specific to AWS Aurora PostgreSQL and Semantic Triples to MarkLogic — each maps to any object or custom field on the other side.
Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. TDE Views Relational projections of documents that let syncs read document data as SQL rows. Columns is specific to AWS Aurora PostgreSQL and TDE Views to MarkLogic — each maps to any object or custom field on the other side.
Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. Document Metadata & Properties Permissions, quality, and property fragments carried with each document. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Document Metadata & Properties to MarkLogic — each maps to any object or custom field on the other side.
Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. Databases & Forests Storage units that define the scope and placement of synced content. Views and materialized views is specific to AWS Aurora PostgreSQL and Databases & Forests to MarkLogic — each maps to any object or custom field on the other side.
Foreign keys Relationship metadata that syncs can translate into object references elsewhere. Users & Roles Security principals that govern what an integration credential can read or write. Foreign keys is specific to AWS Aurora PostgreSQL and Users & Roles to MarkLogic — each maps to any object or custom field on the other side.
Replication slots and publications The logical replication objects that power log-based CDC. Documents JSON and XML documents, the primary records read from and written to the database. Replication slots and publications is specific to AWS Aurora PostgreSQL and Documents to MarkLogic — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL and MarkLogic

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.

AWS Aurora PostgreSQL MarkLogic Sub-second propagation

DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.

DeliveryEach detected change is applied to MarkLogic as a row-level write, with types converted between the two schemas.

MarkLogic AWS Aurora PostgreSQL Interval-based propagation

DetectionStacksync polls MarkLogic for changes on an incremental schedule, reading only records changed since the previous pass. No exposed transaction log.

DeliveryEach detected change is applied to AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.

What ships with AWS Aurora PostgreSQL ⇄ MarkLogic

Connect AWS Aurora PostgreSQL and MarkLogic for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–MarkLogic connection.

Real-time

Two-way sync

Changes in AWS Aurora PostgreSQL or MarkLogic instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora PostgreSQL or MarkLogic 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 AWS Aurora PostgreSQL or MarkLogic record.

Observability

Monitoring

Track your AWS Aurora PostgreSQL ⇄ MarkLogic sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and MarkLogic.

How the AWS Aurora PostgreSQL and MarkLogic connectors work

AWS Aurora PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
Capabilities
read · write · CDC

MarkLogic

Integration surface
REST API (Client API), plus SQL/ODBC access over TDE views and Java/Node client libraries
Authentication
Username/password (digest or basic), with certificate-based options
Change detection
No exposed transaction log; polling on document timestamps/metadata, or server-side triggers that record changes for pickup
Capabilities
read · write
How it works

How to connect AWS Aurora PostgreSQL to MarkLogic — 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 AWS Aurora PostgreSQL and MarkLogic 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
    AWS Aurora PostgreSQL connected
    MarkLogic connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora PostgreSQL and MarkLogic 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 · AWS Aurora PostgreSQL ⇄ MarkLogic
    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
    AWS Aurora PostgreSQL MarkLogic
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora PostgreSQL and MarkLogic 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
CSA STAR
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 392 integrations available for AWS Aurora PostgreSQL and MarkLogic.

Popular · 8 of 392
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