Real-time
Two-way sync
Changes in Jira or Scaleway Postgres instantly reflect in both systems. No stale data, no manual imports.
Developer tools ⇄ Database
Jira to Scaleway Postgres integration — real-time, two-way sync
Keep Jira and Scaleway Postgres 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 Jira and Scaleway Postgres
Keep Scaleway Postgres and Jira in step: the rows in your database and the Components, Users, Issues, Projects your engineering tools track stay consistent in real time, in both directions.
Scaleway Postgres 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 Columns, Tables, Views, Materialized views in Scaleway Postgres with Components, Users, Issues, Projects 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.
Common use cases
- 01 Sync production tables from Scaleway Postgres into a CRM so sales and support see live product usage on customer records
- 02 Run a two-way sync between Scaleway Postgres and SaaS tools so edits made in either system converge on the same rows
- 03 Load Issues, Worklogs, and status transitions into a warehouse for cycle-time, throughput, and burndown reporting.
- 04 Sync Sprints and Boards with a capacity-planning tool so estimates and iteration scope stay aligned.
Common sync patterns
Land tool activity as queryable rows
Records and events from Jira arrive in Scaleway Postgres as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.
One integration pattern instead of per-tool API code
Read and write the synced tables in Scaleway Postgres and Stacksync keeps Jira current, replacing the auth, webhooks, rate limits, and retry logic you would otherwise maintain for each tool.
React to changes on either side in near real time
Updates in Jira arrive as row changes in Scaleway Postgres, and writes to Scaleway Postgres propagate to Jira within seconds, so triggers, jobs, and alerts fire without polling.
What you can sync between Jira and Scaleway Postgres
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 | Scaleway Postgres objects | How this pairing syncs | |
|---|---|---|---|
| Users Account records referenced as reporters, assignees, and watchers; read to resolve accountId to a person when mapping Issue ownership. | Schemas Namespace tables so multiple applications or environments can be synced selectively. | Users is specific to Jira and Schemas to Scaleway Postgres — each maps to any object or custom field on the other side. | |
| 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. | Sequences Generate primary keys; sync tooling must respect them when writing rows. | Issues is specific to Jira and Sequences to Scaleway Postgres — 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. | Columns Postgres-native types, including JSONB and arrays, are mapped to fields in the paired system. | Projects is specific to Jira and Columns to Scaleway Postgres — 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. | Tables Primary sync unit; each table maps to an object or table on the other side of the sync. | Comments is specific to Jira and Tables to Scaleway Postgres — 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. | Views Read-only sources for shaping data before it leaves the database. | Worklogs is specific to Jira and Views to Scaleway Postgres — 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. | Materialized views Precomputed result sets that can be read on a schedule for downstream syncs. | Sprints is specific to Jira and Materialized views to Scaleway Postgres — each maps to any object or custom field on the other side. |
How changes propagate between Jira and Scaleway Postgres
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.
Jira Scaleway Postgres Sub-second propagation
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 Scaleway Postgres as a row-level write, with types converted between the two schemas.
Scaleway Postgres Jira Sub-second propagation
DetectionChanges in Scaleway Postgres are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication where the managed instance permits it.
DeliveryEach detected change is written to Jira through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Jira: Cost-based (points) model; 429 responses return Retry-After and X-RateLimit-* headers. JQL search costs far more than single-issue reads.
- Scaleway Postgres: Throughput is bounded by instance size and connection limits rather than API quotas.
What ships with Jira ⇄ Scaleway Postgres
Connect Jira and Scaleway Postgres for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Jira–Scaleway Postgres connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Jira or Scaleway Postgres 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 Jira or Scaleway Postgres record.
Observability
Monitoring
Track your Jira ⇄ Scaleway Postgres sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Jira and Scaleway Postgres.
How the Jira and Scaleway Postgres connectors work
Jira
- Integration surface
- 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
- Change detection
- 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.
- Capabilities
- read · write · webhooks
- Rate limits
- Cost-based (points) model; 429 responses return Retry-After and X-RateLimit-* headers. JQL search costs far more than single-issue reads.
Scaleway Postgres
- Integration surface
- SQL wire protocol (PostgreSQL)
- Authentication
- Database credentials (username/password over TLS)
- Change detection
- Log-based CDC via PostgreSQL logical replication where the managed instance permits it; otherwise timestamp or query-based polling
- Capabilities
- read · write · CDC
- Rate limits
- Throughput is bounded by instance size and connection limits rather than API quotas
How it works
How to connect Jira to Scaleway Postgres — 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 Jira and Scaleway Postgres with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Jira
connected
Scaleway Postgres
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Jira and Scaleway Postgres 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 · Jira ⇄ Scaleway PostgresCustomers 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.
Jira Scaleway PostgresCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Jira and Scaleway Postgres integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Jira and Scaleway Postgres: authenticate both systems, choose the objects to sync (such as Jira's Users and Issues), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Yes — Stacksync ships production-grade connectors for both Jira and Scaleway Postgres. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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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 Scaleway Postgres: Log-based CDC via PostgreSQL logical replication where the managed instance permits it; otherwise timestamp or query-based polling. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
-
On the Scaleway Postgres side: Columns, Tables, Views, Materialized views, plus custom fields where Scaleway Postgres exposes them. On the Jira side: Components, Users, Issues, Projects. 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 Jira and Scaleway Postgres: Land tool activity as queryable rows; One integration pattern instead of per-tool API code; React to changes on either side in near real time. Records and events from Jira arrive in Scaleway Postgres as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 322 integrations available for Jira and Scaleway Postgres.
Popular · 7 of 322
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Jira ⇄ AWS Aurora MySQL - Jira ⇄ AWS Aurora PostgreSQL
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Jira ⇄ MongoDB -
Jira ⇄ CockroachDB -
Scaleway Postgres ⇄ Jms -
Scaleway Postgres ⇄ Newrelic -
Scaleway Postgres ⇄ Opsgenie
No integrations match .
