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Database

Azure SQL Database to Elasticsearch integration — real-time, two-way sync

Keep Azure SQL Database 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 Azure SQL Database and Elasticsearch

Keep Azure SQL Database and Elasticsearch 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 Azure SQL Database and Elasticsearch 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 Expose SaaS data (billing, support tickets) as tables in Azure SQL for reporting teams already on Microsoft tooling.
  • 02 Replicate Azure SQL tables to a warehouse without building custom CDC pipelines.
  • 03 Sync CRM accounts and contacts into an Elasticsearch index to power internal search across customer records.
  • 04 Push product catalog data from an ERP or commerce database into Elasticsearch for storefront search.

Common sync patterns

Regional or environment copies

Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.

Cross-engine sync

Keep the same dataset live in both Azure SQL Database and Elasticsearch, 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.

What you can sync between Azure SQL Database 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.

Azure SQL Database objects Elasticsearch objects How this pairing syncs
Change tracking / CDC tables System-maintained change records used to drive incremental sync. Index templates Reusable settings and mappings applied automatically to new indices a sync creates. Change tracking / CDC tables is specific to Azure SQL Database and Index templates to Elasticsearch — each maps to any object or custom field on the other side.
Tables The primary sync target; rows map one-to-one to records in the paired system. Indices Target containers for synced records; each holds a table-like collection of JSON documents. Tables is specific to Azure SQL Database and Indices to Elasticsearch — each maps to any object or custom field on the other side.
Views Read-only projections used when the sync should expose a curated shape rather than raw tables. Documents The unit of sync; JSON records created, updated, and deleted by _id. Views is specific to Azure SQL Database and Documents to Elasticsearch — each maps to any object or custom field on the other side.
Schemas Namespaces that organize tables and control which objects a sync user can reach. Index mappings Field type definitions that determine how synced fields are indexed and queried. Schemas is specific to Azure SQL Database and Index mappings to Elasticsearch — each maps to any object or custom field on the other side.
Rows and columns Standard relational records with typed columns; primary keys anchor upserts. Aliases Stable read/write names that let a sync cut over between index versions without downtime. Rows and columns is specific to Azure SQL Database and Aliases to Elasticsearch — each maps to any object or custom field on the other side.
Stored procedures Existing business logic that some teams invoke on write instead of direct table inserts. Data streams Append-only targets for time-series or event data pushed from source systems. Stored procedures is specific to Azure SQL Database and Data streams to Elasticsearch — each maps to any object or custom field on the other side.

How changes propagate between Azure SQL Database 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.

Azure SQL Database Elasticsearch Sub-second propagation

DetectionChanges in Azure SQL Database are captured at the source via change data capture — no polling loop against its API. Change data capture or change tracking, both supported on Azure SQL Database.

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

Elasticsearch Azure SQL Database 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 applied to Azure SQL Database as a row-level write, with types converted between the two schemas.

Rate-limit considerations

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

Connect Azure SQL Database and Elasticsearch for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure SQL Database–Elasticsearch connection.

Real-time

Two-way sync

Changes in Azure SQL Database or Elasticsearch instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure SQL Database 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 Azure SQL Database or Elasticsearch record.

Observability

Monitoring

Track your Azure SQL Database ⇄ Elasticsearch sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Azure SQL Database and Elasticsearch.

How the Azure SQL Database and Elasticsearch connectors work

Azure SQL Database

Integration surface
SQL wire protocol (TDS), the same protocol as SQL Server; T-SQL over standard drivers
Authentication
SQL authentication (database credentials) or Microsoft Entra ID authentication
Change detection
Change data capture or change tracking, both supported on Azure SQL Database; polling as a fallback
Capabilities
read · write · CDC

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 Azure SQL Database 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 Azure SQL Database 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
    Azure SQL Database connected
    Elasticsearch connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Azure SQL Database 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 · Azure SQL Database ⇄ 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
    Azure SQL Database Elasticsearch
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Azure SQL Database 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.

Learn more about security
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:

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 457 integrations available for Azure SQL Database and Elasticsearch.

Popular · 5 of 457
All Azure SQL Database integrations All Elasticsearch integrations Browse all integrations
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