Two-way sync
Changes in Elasticsearch or MarkLogic instantly reflect in both systems. No stale data, no manual imports.
Keep Elasticsearch 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.
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 Elasticsearch 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.
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Keep the same dataset live in both Elasticsearch and MarkLogic, so each workload runs on the engine that suits it.
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.
| Elasticsearch objects | MarkLogic objects | How this pairing syncs | |
|---|---|---|---|
| Documents The unit of sync; JSON records created, updated, and deleted by _id. | Documents JSON and XML documents, the primary records read from and written to the database. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Data streams Append-only targets for time-series or event data pushed from source systems. | Semantic Triples RDF data stored alongside documents, queryable with SPARQL for linked-data syncs. | Data streams is specific to Elasticsearch and Semantic Triples to MarkLogic — each maps to any object or custom field on the other side. | |
| Ingest pipelines Server-side transforms applied to documents as a sync writes them. | TDE Views Relational projections of documents that let syncs read document data as SQL rows. | Ingest pipelines is specific to Elasticsearch and TDE Views to MarkLogic — each maps to any object or custom field on the other side. | |
| Index templates Reusable settings and mappings applied automatically to new indices a sync creates. | Document Metadata & Properties Permissions, quality, and property fragments carried with each document. | Index templates is specific to Elasticsearch and Document Metadata & Properties to MarkLogic — each maps to any object or custom field on the other side. | |
| Indices Target containers for synced records; each holds a table-like collection of JSON documents. | Databases & Forests Storage units that define the scope and placement of synced content. | Indices is specific to Elasticsearch and Databases & Forests to MarkLogic — each maps to any object or custom field on the other side. | |
| Index mappings Field type definitions that determine how synced fields are indexed and queried. | Users & Roles Security principals that govern what an integration credential can read or write. | Index mappings is specific to Elasticsearch and Users & Roles to MarkLogic — 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.
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 applied to MarkLogic as a row-level write, with types converted between the two schemas.
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 written to Elasticsearch through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Elasticsearch–MarkLogic connection.
Changes in Elasticsearch or MarkLogic instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Elasticsearch or MarkLogic data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Elasticsearch or MarkLogic record.
Track your Elasticsearch ⇄ MarkLogic sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Elasticsearch and MarkLogic.
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 Elasticsearch 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.
Pick the Elasticsearch 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.
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 Elasticsearch and MarkLogic: authenticate both systems, choose the objects to sync (such as Elasticsearch's Documents and Data streams), 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 Elasticsearch and MarkLogic connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Elasticsearch–MarkLogic integration in-house.
Yes — Stacksync ships production-grade connectors for both Elasticsearch and MarkLogic. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Elasticsearch: Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks. On MarkLogic: No exposed transaction log; polling on document timestamps/metadata, or server-side triggers that record changes for pickup. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Elasticsearch side: Documents, Index mappings, Aliases, Data streams, plus custom fields where Elasticsearch exposes them. On the MarkLogic side: Semantic Triples, TDE Views, Document Metadata & Properties, Databases & Forests. 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 392 integrations available for Elasticsearch and MarkLogic.