Skip to content
Database ⇄ Developer tools

Google Cloud Spanner to Jira integration — real-time, two-way sync

Keep Google Cloud Spanner and Jira 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

Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Google Cloud Spanner and Jira

Keep Google Cloud Spanner and Jira in step: the rows in your database and the Users, Issues, Projects, Comments your engineering tools track stay consistent in real time, in both directions.

Google Cloud Spanner 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 Rows, Interleaved tables, Secondary indexes, Change streams in Google Cloud Spanner with Users, Issues, Projects, Comments 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 Consolidate data from a globally distributed Spanner deployment into regional business systems.
  • 02 Push billing or entitlement changes from finance tools into Spanner tables the application reads at runtime.
  • 03 Consolidate multiple Jira Projects or sites into one database, mapping Projects, Components, and Versions for cross-team reporting.
  • 04 Two-way sync Issues and their status, assignee, and story points with a Postgres database so teams query and update sprint data in SQL.

Common sync patterns

One integration pattern instead of per-tool API code

Read and write the synced tables in Google Cloud Spanner 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 Google Cloud Spanner, and writes to Google Cloud Spanner propagate to Jira within seconds, so triggers, jobs, and alerts fire without polling.

Where Jira manages users or groups: keep identity aligned

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

What you can sync between Google Cloud Spanner and Jira

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.

Google Cloud Spanner objects Jira objects How this pairing syncs
Rows The unit of read and write in each sync cycle, keyed by primary key. Worklogs Time-tracking entries against Issues; read into warehouses for effort and capacity reporting, or written back from timesheet tools. Rows is specific to Google Cloud Spanner and Worklogs to Jira — each maps to any object or custom field on the other side.
Interleaved tables Child rows physically co-located with parents; synced as related records. Sprints Agile iterations from the Jira Software API; synced to report scope, velocity, and burndown, and to move Issues between sprints. Interleaved tables is specific to Google Cloud Spanner and Sprints to Jira — each maps to any object or custom field on the other side.
Secondary indexes Used to make incremental read queries efficient on non-key columns. Versions Release / fix-version records per Project; synced to align roadmap and release tools on what ships in each version. Secondary indexes is specific to Google Cloud Spanner and Versions to Jira — each maps to any object or custom field on the other side.
Change streams Capture inserts, updates, and deletes for log-style change data capture. Components Sub-project categories used to route and group Issues; synced so ownership and triage stay consistent across tools. Change streams is specific to Google Cloud Spanner and Components to Jira — each maps to any object or custom field on the other side.
Views Read-only projections useful for shaping data before it leaves Spanner. Users Account records referenced as reporters, assignees, and watchers; read to resolve accountId to a person when mapping Issue ownership. Views is specific to Google Cloud Spanner and Users to Jira — each maps to any object or custom field on the other side.
Databases Top-level containers that scope schema and sync configuration. 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 is specific to Google Cloud Spanner and Issues to Jira — each maps to any object or custom field on the other side.

How changes propagate between Google Cloud Spanner and Jira

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.

Google Cloud Spanner Jira Sub-second propagation

DetectionChanges in Google Cloud Spanner are captured at the source via change data capture — no polling loop against its API. Change streams (log-style CDC), or timestamp-based polling queries.

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

Jira Google Cloud Spanner 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 Google Cloud Spanner as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Google Cloud Spanner: Throughput is bounded by the instance's provisioned compute capacity rather than a fixed API quota.
  • Jira: Cost-based (points) model; 429 responses return Retry-After and X-RateLimit-* headers. JQL search costs far more than single-issue reads.
What ships with Google Cloud Spanner ⇄ Jira

Connect Google Cloud Spanner and Jira for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Google Cloud Spanner or Jira 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 Google Cloud Spanner or Jira record.

Observability

Monitoring

Track your Google Cloud Spanner ⇄ Jira sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Google Cloud Spanner and Jira.

How the Google Cloud Spanner and Jira connectors work

Google Cloud Spanner

Integration surface
gRPC/REST client API with SQL query surface (GoogleSQL and PostgreSQL-interface dialects)
Authentication
Google Cloud IAM (service accounts)
Change detection
Change streams (log-style CDC), or timestamp-based polling queries
Capabilities
read · write · CDC
Rate limits
Throughput is bounded by the instance's provisioned compute capacity rather than a fixed API quota.

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.
How it works

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

    Choose tables

    Pick the Google Cloud Spanner and Jira 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 · Google Cloud Spanner ⇄ Jira
    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
    Google Cloud Spanner Jira
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Google Cloud Spanner and Jira 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 306 integrations available for Google Cloud Spanner and Jira.

Popular · 7 of 306
All Google Cloud Spanner integrations All Jira integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own