Two-way sync
Changes in Elasticsearch or SQL Server instantly reflect in both systems. No stale data, no manual imports.
Keep Elasticsearch and SQL Server 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 SQL Server 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.
Keep the same dataset live in both Elasticsearch and SQL Server, so each workload runs on the engine that suits it.
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
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 | SQL Server objects | |
|---|---|---|
| Documents The unit of sync; JSON records created, updated, and deleted by _id. | CDC Change Tables System-populated tables holding captured inserts, updates, and deletes for consumers. | |
| Index mappings Field type definitions that determine how synced fields are indexed and queried. | Stored Procedures T-SQL logic that can validate or post-process synced rows. | |
| Aliases Stable read/write names that let a sync cut over between index versions without downtime. | Databases Instance-level databases that scope a sync's reads and writes. | |
| Data streams Append-only targets for time-series or event data pushed from source systems. | Schemas Namespaces (dbo and custom) used to organize synced tables. | |
| Ingest pipelines Server-side transforms applied to documents as a sync writes them. | Tables The primary sync target; rows map to records in connected systems. | |
| Index templates Reusable settings and mappings applied automatically to new indices a sync creates. | Views Read-side projections used as outbound sync sources. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Elasticsearch–SQL Server connection.
Changes in Elasticsearch or SQL Server instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Elasticsearch or SQL Server 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 SQL Server record.
Track your Elasticsearch ⇄ SQL Server sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Elasticsearch and SQL Server.
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 SQL Server 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 SQL Server 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 SQL Server: authenticate both systems, choose the objects to sync (such as Elasticsearch's Documents and Index mappings), 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 SQL Server connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Elasticsearch–SQL Server integration in-house.
Yes — Stacksync ships production-grade connectors for both Elasticsearch and SQL Server. 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 SQL Server: SQL Server Native Change Data Capture (CDC); a DBA runs a one-time setup script with sysadmin privileges to enable CDC and create Stacksync wrapper procedures. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Elasticsearch side: Ingest pipelines, Index templates, Indices, Documents, plus custom fields where Elasticsearch exposes them. On the SQL Server side: Databases, Schemas, Tables, Views. 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 386 integrations available for Elasticsearch and SQL Server.