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Jira to TimescaleDB integration — real-time, two-way sync

Keep Jira and TimescaleDB 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 TimescaleDB

Keep TimescaleDB and Jira in step: the rows in your database and the Comments, Worklogs, Sprints, Versions your engineering tools track stay consistent in real time, in both directions.

TimescaleDB 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 Schemas, Hypertables, Chunks, Continuous Aggregates in TimescaleDB with Comments, Worklogs, Sprints, Versions 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 Keep device or asset reference tables bi-directionally in sync between TimescaleDB and an ERP.
  • 02 Consolidate metrics from several services into one hypertable to serve a single reporting layer.
  • 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

Where Jira manages users or groups: keep identity aligned

Directory and identity records in Jira stay matched to the users or owners table in TimescaleDB, so provisioning and de-provisioning flow from one source.

Turn rows into the records your tools track

A new or changed row in TimescaleDB 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.

Land tool activity as queryable rows

Records and events from Jira arrive in TimescaleDB as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.

What you can sync between Jira and TimescaleDB

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 TimescaleDB objects How this pairing syncs
Sprints Agile iterations from the Jira Software API; synced to report scope, velocity, and burndown, and to move Issues between sprints. Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. Sprints is specific to Jira and Continuous Aggregates to TimescaleDB — 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. Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. Versions is specific to Jira and Regular PostgreSQL Tables to TimescaleDB — each maps to any object or custom field on the other side.
Components Sub-project categories used to route and group Issues; synced so ownership and triage stay consistent across tools. Views Standard SQL views used to shape or filter data for consumers. Components is specific to Jira and Views to TimescaleDB — each maps to any object or custom field on the other side.
Users Account records referenced as reporters, assignees, and watchers; read to resolve accountId to a person when mapping Issue ownership. Schemas Postgres namespaces used to separate synced datasets by team or environment. Users is specific to Jira and Schemas to TimescaleDB — 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. Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. Issues is specific to Jira and Hypertables to TimescaleDB — 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. Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. Projects is specific to Jira and Chunks to TimescaleDB — each maps to any object or custom field on the other side.

How changes propagate between Jira and TimescaleDB

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 TimescaleDB 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 TimescaleDB as a row-level write, with types converted between the two schemas.

TimescaleDB Jira Sub-second propagation

DetectionChanges in TimescaleDB are captured at the source via change data capture — no polling loop against its API. Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must.

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.
  • TimescaleDB: No API rate limits; throughput is bounded by database resources and connection limits.
What ships with Jira ⇄ TimescaleDB

Connect Jira and TimescaleDB for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Jira–TimescaleDB connection.

Real-time

Two-way sync

Changes in Jira or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Jira or TimescaleDB 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 TimescaleDB record.

Observability

Monitoring

Track your Jira ⇄ TimescaleDB 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 TimescaleDB.

How the Jira and TimescaleDB 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.

TimescaleDB

Integration surface
SQL wire protocol (PostgreSQL)
Authentication
Database credentials
Change detection
Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by database resources and connection limits.
How it works

How to connect Jira to TimescaleDB — 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 Jira and TimescaleDB 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
    Jira connected
    TimescaleDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Jira and TimescaleDB 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 · Jira ⇄ TimescaleDB
    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
    Jira TimescaleDB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Jira and TimescaleDB 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
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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 308 integrations available for Jira and TimescaleDB.

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