Skip to content
Developer tools ⇄ Data warehouse

Jms to Tinybird integration — real-time, two-way sync

Keep Jms and Tinybird 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 Jms and Tinybird

Close the gap between analytics and operations: Tinybird holds the record while Jms runs the day-to-day work, and Stacksync keeps the two in step in real time, in both directions.

Tinybird is the central store where teams keep Materialized Views, Workspaces, Tokens, Data Sources for reporting and analysis; Jms runs the operational side of engineering work — tracking issues, moving messages and events, watching systems, and managing users and access. The two overlap wherever the same operational data matters to both: the Queue, Topic, TextMessage, MapMessage produced in Jms are exactly what analysts want to measure in Tinybird, and the curated rows in Tinybird are what should drive the next action in Jms. When that overlap is bridged by nightly ETL or hand-written scripts, dashboards lag a day behind reality and the tools that should react to warehouse signals never see them.

Stacksync syncs Materialized Views, Workspaces, Tokens, Data Sources in Tinybird with Queue, Topic, TextMessage, MapMessage in Jms field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync matches records on a stable external key, keeps every copy consistent, and resolves conflicts by rules you set — so analytics and operations work from the same current data instead of two drifting copies.

Common use cases

  • 01 Sync order events from an ERP into Tinybird to serve low-latency operational analytics endpoints.
  • 02 Compute aggregates in Tinybird and write the results back to CRM fields for scoring and routing.
  • 03 Consume order or event messages from a JMS Queue and upsert them as rows into Postgres or a warehouse so downstream apps read them in plain SQL.
  • 04 Publish records changed in a CRM or database as TextMessages onto a JMS Topic so subscribing Java services react in real time.

Common sync patterns

Backfill history, then stay live

Load the existing set of Queue, Topic, TextMessage, MapMessage into Tinybird once, then keep it current with every change — you get full history plus real-time updates without a separate pipeline.

No batch jobs to babysit

New and changed records move field by field the moment they change, replacing scheduled ETL and one-off scripts that fail quietly and leave stale rows behind.

One shared record, kept consistent

Where both systems track the same entity, a change on either side propagates to the other, ending the manual reconciliation between the operational copy and the warehouse copy.

What you can sync between Jms and Tinybird

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.

Jms objects Tinybird objects How this pairing syncs
TextMessage Most common body type, carrying a String that is usually JSON or XML. Deserialized into rows/records on read and serialized from source records on write. Tokens Scoped credentials that control read and append rights per resource. TextMessage is specific to Jms and Tokens to Tinybird — each maps to any object or custom field on the other side.
MapMessage Body of typed name/value pairs that maps directly onto record fields, so no custom body parsing is needed on read or write. Data Sources ClickHouse-backed tables that receive ingested rows; the write target for syncs into Tinybird. MapMessage is specific to Jms and Data Sources to Tinybird — each maps to any object or custom field on the other side.
BytesMessage Raw binary body for files, protobuf, or opaque payloads; passed through as a byte stream when structured field mapping is not required. Pipes Chained SQL nodes that transform Data Sources into query-ready results. BytesMessage is specific to Jms and Pipes to Tinybird — each maps to any object or custom field on the other side.
Durable Subscription Named topic subscription that retains messages while the consumer is offline, so a sync that disconnects does not miss events published in the meantime. API Endpoints Published Pipe outputs exposed as parameterized HTTP queries; the main read surface. Durable Subscription is specific to Jms and API Endpoints to Tinybird — each maps to any object or custom field on the other side.
Message headers and properties JMSCorrelationID, JMSReplyTo, JMSTimestamp, JMSType plus JMSX/application-defined properties; used for correlation, routing, and selector-based filtering. Materialized Views Pipes materialized into new Data Sources for pre-aggregation at ingest time. Message headers and properties is specific to Jms and Materialized Views to Tinybird — each maps to any object or custom field on the other side.
Dead Letter Queue Provider-managed destination (e.g. ActiveMQ.DLQ, IBM MQ dead-letter queue) where messages exceeding redelivery limits land; read to reconcile failed deliveries. Workspaces Project boundary that scopes Data Sources, Pipes, and tokens for a sync. Dead Letter Queue is specific to Jms and Workspaces to Tinybird — each maps to any object or custom field on the other side.

How changes propagate between Jms and Tinybird

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.

Jms Tinybird Sub-second propagation

DetectionJms notifies Stacksync of record changes through webhook events. Asynchronous push — the broker delivers messages to registered consumers (MessageListener.onMessage) in real time, with no polling.

DeliveryEach detected change is applied to Tinybird as a row-level write, with types converted between the two schemas.

Tinybird Jms Interval-based propagation

DetectionStacksync polls Tinybird for changes on an incremental schedule, reading only records changed since the previous pass. Append-oriented ingestion.

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

Rate-limit considerations

  • Jms: JMS defines no protocol-level rate limits; throughput ceilings, consumer prefetch, and producer flow control are configured on the broker (ActiveMQ, IBM MQ, Solace, TIBCO EMS, etc.).
  • Tinybird: Subject to the platform's ingestion and query rate limits; batch appends where possible.
What ships with Jms ⇄ Tinybird

Connect Jms and Tinybird for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Jms or Tinybird instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Jms or Tinybird 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 Jms or Tinybird record.

Observability

Monitoring

Track your Jms ⇄ Tinybird sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Jms and Tinybird.

How the Jms and Tinybird connectors work

Jms

Integration surface
JMS / Jakarta Messaging API (classic API and simplified JMSContext) over provider transports such as OpenWire, AMQP, IBM MQ, or STOMP
Authentication
Username/password credentials passed to ConnectionFactory.createConnection(); ConnectionFactory and Destinations resolved via JNDI. Transport security (TLS) and stronger auth (SASL, JAAS, client certificates) are broker-implementation-specific.
Change detection
Asynchronous push — the broker delivers messages to registered consumers (MessageListener.onMessage) in real time, with no polling. Message selectors (an SQL-92 subset over headers/properties) filter delivery. There is no modified-date polling or CDC replay, and queue consumption is destructive.
Capabilities
read · write · webhooks
Rate limits
JMS defines no protocol-level rate limits; throughput ceilings, consumer prefetch, and producer flow control are configured on the broker (ActiveMQ, IBM MQ, Solace, TIBCO EMS, etc.).

Tinybird

Integration surface
REST API (Events API for ingestion, published query endpoints) with a ClickHouse SQL dialect
Authentication
Scoped auth tokens
Change detection
Append-oriented ingestion; reads are pulled by querying published endpoints, no outbound CDC
Capabilities
read · write
Rate limits
Subject to the platform's ingestion and query rate limits; batch appends where possible.
How it works

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

    Choose tables

    Pick the Jms and Tinybird 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 · Jms ⇄ Tinybird
    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
    Jms Tinybird
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Jms and Tinybird 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 310 integrations available for Jms and Tinybird.

Popular · 7 of 310
All Jms integrations All Tinybird 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