Two-way sync
Changes in Jira or MariaDB instantly reflect in both systems. No stale data, no manual imports.
Keep Jira and MariaDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
MariaDB is where your application's durable data lives; Jira is where engineering and operations teams track the issues, events, messages, or identities that run alongside it. The two overlap constantly, a row should open a ticket, an alert should land as a record, a user in one should exist in the other, but bridging them today means per-tool integration code: auth, webhooks, pagination, rate limits, and retries, built and maintained separately for every tool.
Stacksync syncs Databases (Schemas), Tables, Views, Columns in MariaDB with Projects, Comments, Worklogs, Sprints in Jira field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set, so the database and the tooling around it never drift apart.
A new or changed row in MariaDB creates or updates the matching record in Jira, whether that is an issue, an event, a message, or a user, so the tool reflects the database without a custom API job.
Records and events from Jira arrive in MariaDB as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.
Read and write the synced tables in MariaDB and Stacksync keeps Jira current, replacing the auth, webhooks, rate limits, and retry logic you would otherwise maintain for each tool.
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.
| Jira objects | MariaDB objects | How this pairing syncs | |
|---|---|---|---|
| Issues Core work items (stories, bugs, tasks, epics, sub-tasks); synced two-way with databases and other trackers, keyed by issue key with an updated field for incrementals. | Databases (Schemas) Top-level namespaces that scope a sync's reads and writes. | Issues is specific to Jira and Databases (Schemas) to MariaDB — each maps to any object or custom field on the other side. | |
| Projects Containers that group Issues, workflows, and permissions; usually read to segment syncs by team, or written when standing up a new project. | Tables The primary sync target; rows map to records in connected systems. | Projects is specific to Jira and Tables to MariaDB — each maps to any object or custom field on the other side. | |
| Comments Discussion threads on Issues; in v3 the body is Atlassian Document Format JSON, so rich text is preserved when syncing to and from other systems. | Views Read-side projections used as outbound sync sources. | Comments is specific to Jira and Views to MariaDB — each maps to any object or custom field on the other side. | |
| Worklogs Time-tracking entries against Issues; read into warehouses for effort and capacity reporting, or written back from timesheet tools. | Columns Field-level mapping targets with engine-typed values. | Worklogs is specific to Jira and Columns to MariaDB — each maps to any object or custom field on the other side. | |
| Sprints Agile iterations from the Jira Software API; synced to report scope, velocity, and burndown, and to move Issues between sprints. | Primary and Unique Keys Match keys for idempotent upserts. | Sprints is specific to Jira and Primary and Unique Keys to MariaDB — each maps to any object or custom field on the other side. | |
| Versions Release / fix-version records per Project; synced to align roadmap and release tools on what ships in each version. | System-Versioned Tables Temporal tables that retain row history natively, useful for auditing synced changes. | Versions is specific to Jira and System-Versioned Tables to MariaDB — 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.
DetectionJira notifies Stacksync of record changes through webhook events. Jira webhooks (jira:issue_created / _updated / _deleted plus comment and worklog events) for near-real-time.
DeliveryEach detected change is applied to MariaDB as a row-level write, with types converted between the two schemas.
DetectionChanges in MariaDB are captured at the source via change data capture — no polling loop against its API. Database triggers — Stacksync creates deterministic triggers for internal logging and syncing.
DeliveryEach detected change is written to Jira through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Jira–MariaDB connection.
Changes in Jira or MariaDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Jira or MariaDB data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Jira or MariaDB record.
Track your Jira ⇄ MariaDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Jira and MariaDB.
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 Jira and MariaDB 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 Jira and MariaDB 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 Jira and MariaDB: authenticate both systems, choose the objects to sync (such as Jira's Issues and Projects), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Jira: Jira webhooks (jira:issue_created / _updated / _deleted plus comment and worklog events) for near-real-time; incremental JQL polling on the issue updated timestamp as a best-effort reconciliation fallback. On MariaDB: Database triggers — Stacksync creates deterministic triggers for internal logging and syncing. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the MariaDB side: Databases (Schemas), Tables, Views, Columns, plus custom fields where MariaDB exposes them. On the Jira side: Projects, Comments, Worklogs, Sprints. 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.
Common patterns for Jira and MariaDB: Turn rows into the records your tools track; Land tool activity as queryable rows; One integration pattern instead of per-tool API code. A new or changed row in MariaDB creates or updates the matching record in Jira, whether that is an issue, an event, a message, or a user, so the tool reflects the database without a custom API job.
Jira: REST API v2 and v3 plus the Jira Software (Agile) REST API. Authentication: OAuth 2.0 (3LO) for apps, or Basic auth with an Atlassian account email plus API token. MariaDB: SQL wire protocol (MySQL-compatible client/server protocol). Authentication: Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host). Stacksync manages authentication, retries, and rate limits on both sides.
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 322 integrations available for Jira and MariaDB.