Real-time
Two-way sync
Changes in Atlassian or Elasticsearch instantly reflect in both systems. No stale data, no manual imports.
Business productivity ⇄ Database
Atlassian to Elasticsearch integration — real-time, two-way sync
Keep Atlassian 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.
- 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 Atlassian and Elasticsearch
Mirror Atlassian's data into Elasticsearch so your own code can read and write it like any other table, with changes flowing both ways in seconds.
Engineers integrate with tools like Atlassian through APIs, which means auth, pagination, rate limits, webhooks, and retry logic, all maintained forever and all different for every tool. Meanwhile the data would be trivial to use if it simply lived in Elasticsearch.
Stacksync mirrors Users and Groups, Confluence Pages, Confluence Spaces, Jira Issues from Atlassian into Aliases, Data streams, Ingest pipelines, Index templates in Elasticsearch and keeps both sides in sync in real time. Your services query the database directly, and inserts or updates your code makes flow back into Atlassian, so the tool and the database never disagree.
Common use cases
- Keep Jira and a second tracker (for example a customer's Jira instance) aligned during co-delivery projects.
- Sync Confluence page metadata into a knowledge index so other tools can link to current documentation.
- Feed enriched customer records into an index used for vector or hybrid search in AI applications.
- Sync CRM accounts and contacts into an Elasticsearch index to power internal search across customer records.
Read Atlassian with a query
Records from Atlassian are ordinary rows in Elasticsearch; join them, index them, and use them in application logic without touching the vendor API.
Automate Atlassian from your codebase
Write to the synced tables in Elasticsearch and Stacksync propagates the change into Atlassian, replacing custom integration code.
React to changes as they happen
Updates in Atlassian arrive as row changes in Elasticsearch, so triggers, jobs, and services can respond in near real time.
What you can sync between Atlassian 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.
| Atlassian objects | Elasticsearch objects | |
|---|---|---|
| Boards and Sprints Agile structures read to report on sprint contents and status. | Index mappings Field type definitions that determine how synced fields are indexed and queried. | |
| Issue Comments Threaded discussion synced into linked tickets in external systems. | Aliases Stable read/write names that let a sync cut over between index versions without downtime. | |
| Attachments Files on issues mirrored to paired records where needed. | Data streams Append-only targets for time-series or event data pushed from source systems. | |
| Custom Fields Instance-specific fields (customfield IDs) that carry most business-specific data in syncs. | Ingest pipelines Server-side transforms applied to documents as a sync writes them. | |
| Workflows and Statuses Status transitions mapped to stages in the paired system. | Index templates Reusable settings and mappings applied automatically to new indices a sync creates. | |
| Users and Groups Assignees and reporters matched to identities in other tools. | Indices Target containers for synced records; each holds a table-like collection of JSON documents. |
What ships with Atlassian ⇄ Elasticsearch
Connect Atlassian and Elasticsearch for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Atlassian–Elasticsearch connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Atlassian 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 Atlassian or Elasticsearch record.
Observability
Monitoring
Track your Atlassian ⇄ Elasticsearch sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Atlassian and Elasticsearch.
How the Atlassian and Elasticsearch connectors work
Atlassian
- Integration surface
- REST APIs per product (Jira Cloud and Confluence Cloud)
- Authentication
- OAuth 2.0 (3LO) for apps or API tokens with basic auth for scripts
- Change detection
- Webhooks on issue and page events, plus JQL polling on the updated timestamp for backfill
- Capabilities
- read · write · webhooks
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 Atlassian 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.
- 01
Connect your apps
Authenticate Atlassian 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.
Atlassian
connected
Elasticsearch
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Atlassian 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.
objects · Atlassian ⇄ ElasticsearchCustomers 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.
Atlassian ElasticsearchCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Atlassian and Elasticsearch integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Atlassian and Elasticsearch: authenticate both systems, choose the objects to sync (such as Atlassian's Boards and Sprints and Issue Comments), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the Atlassian side: Users and Groups, Confluence Pages, Confluence Spaces, Jira Issues, plus custom fields where Atlassian exposes them. On the Elasticsearch side: Aliases, Data streams, Ingest pipelines, Index templates. Stacksync auto-detects both schemas and converts types between the two systems.
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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.
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Common patterns for Atlassian and Elasticsearch: Read Atlassian with a query; Automate Atlassian from your codebase; React to changes as they happen. Records from Atlassian are ordinary rows in Elasticsearch; join them, index them, and use them in application logic without touching the vendor API.
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Atlassian: REST APIs per product (Jira Cloud and Confluence Cloud). Authentication: OAuth 2.0 (3LO) for apps or API tokens with basic auth for scripts. Elasticsearch: REST API (JSON over HTTP). Authentication: API keys or basic authentication; Elastic Cloud also issues service account tokens. Stacksync manages authentication, retries, and rate limits on both sides.
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Atlassian: Jira custom fields are identified by instance-specific IDs (customfield_XXXXX), so field mappings must be discovered per site rather than hard-coded. Elasticsearch: Writes are addressed by document _id, so upserts map directly onto the index API, and the _bulk endpoint batches many operations in a single request. Stacksync's field mapping accounts for these differences between Atlassian and Elasticsearch without custom code.
SECURITY
Security teams love 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
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Atlassian and Elasticsearch.
Popular · 8 of 386
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Atlassian ⇄ Dynamo DB -
Atlassian ⇄ IBM Db2 -
Atlassian ⇄ Firebase -
Atlassian ⇄ SingleStore -
Elasticsearch ⇄ SendGrid -
Elasticsearch ⇄ Twilio -
Elasticsearch ⇄ GitHub -
Elasticsearch ⇄ Braze
No integrations match .
