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Data warehouse ⇄ Developer tools

Apache Pinot to Jms integration — real-time, two-way sync

Keep Apache Pinot and Jms 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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Why teams connect Apache Pinot and Jms

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

Apache Pinot is the central store where teams keep Tenants, Tables, Schemas, Segments 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 TextMessage, MapMessage, BytesMessage, Durable Subscription produced in Jms are exactly what analysts want to measure in Apache Pinot, and the curated rows in Apache Pinot 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 Tenants, Tables, Schemas, Segments in Apache Pinot with TextMessage, MapMessage, BytesMessage, Durable Subscription 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 Pinot aggregates into a warehouse to join low-latency metrics with modeled historical data.
  • 02 Serve user-facing analytics from Pinot while syncing daily rollups to finance and ops tools.
  • 03 Publish records changed in a CRM or database as TextMessages onto a JMS Topic so subscribing Java services react in real time.
  • 04 Bridge a legacy IBM MQ or ActiveMQ Queue to a SaaS system of record by consuming each message and writing the record through the SaaS API.

Common sync patterns

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.

Keep user and access records aligned

Where Jms manages users, directory, or access data, those records stay current in Apache Pinot — and can be provisioned back from it — so ownership and permissions match across both.

What you can sync between Apache Pinot and Jms

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.

Apache Pinot objects Jms objects How this pairing syncs
Indexes Inverted, range, and star-tree indexes that determine which sync queries run at low latency. BytesMessage Raw binary body for files, protobuf, or opaque payloads; passed through as a byte stream when structured field mapping is not required. Indexes is specific to Apache Pinot and BytesMessage to Jms — each maps to any object or custom field on the other side.
Tenants Logical groupings that isolate workloads on shared clusters. 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. Tenants is specific to Apache Pinot and Durable Subscription to Jms — each maps to any object or custom field on the other side.
Tables The queryable unit, defined as offline, real-time, or hybrid; the main read target. Message headers and properties JMSCorrelationID, JMSReplyTo, JMSTimestamp, JMSType plus JMSX/application-defined properties; used for correlation, routing, and selector-based filtering. Tables is specific to Apache Pinot and Message headers and properties to Jms — each maps to any object or custom field on the other side.
Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. 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. Schemas is specific to Apache Pinot and Dead Letter Queue to Jms — each maps to any object or custom field on the other side.
Segments Immutable data files that batch ingestion uploads and the cluster serves. Queue Point-to-point destination where each message is delivered to exactly one consumer. Stacksync consumes messages to load into a database, or publishes messages for a downstream Java service to process. Segments is specific to Apache Pinot and Queue to Jms — each maps to any object or custom field on the other side.
Real-time Tables Tables fed continuously from streams like Kafka, including upsert-enabled tables. Topic Publish/subscribe destination that fans each message out to every active subscriber. Stacksync subscribes to event streams or publishes records so multiple services react. Real-time Tables is specific to Apache Pinot and Topic to Jms — each maps to any object or custom field on the other side.

How changes propagate between Apache Pinot and Jms

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.

Apache Pinot Jms Interval-based propagation

DetectionStacksync polls Apache Pinot for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Pinot via streaming ingestion or segment upload, not row-level writes.

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

Jms Apache Pinot 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 Apache Pinot as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Apache Pinot: No fixed API quotas; query throughput depends on broker and server sizing.
  • 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.).
What ships with Apache Pinot ⇄ Jms

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Pinot or Jms 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 Apache Pinot or Jms record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Apache Pinot and Jms connectors work

Apache Pinot

Integration surface
REST API (SQL queries via the broker; administration via the controller); JDBC client available
Authentication
Deployment-dependent: HTTP basic authentication or token-based auth where enabled
Change detection
Not applicable for reads out (polling by time column); data enters Pinot via streaming ingestion or segment upload, not row-level writes
Capabilities
read · write
Rate limits
No fixed API quotas; query throughput depends on broker and server sizing

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.).
How it works

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

    Choose tables

    Pick the Apache Pinot and Jms 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 · Apache Pinot ⇄ Jms
    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
    Apache Pinot Jms
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Apache Pinot and Jms 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.

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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 316 integrations available for Apache Pinot and Jms.

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