Skip to content
Data warehouse ⇄ Developer tools

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

Keep Exasol 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.

  • 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 Exasol and Jms

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

Exasol is the central store where teams keep UDF scripts, Users and roles, Schemas, Tables 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 Durable Subscription, Message headers and properties, Dead Letter Queue, Queue produced in Jms are exactly what analysts want to measure in Exasol, and the curated rows in Exasol 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 UDF scripts, Users and roles, Schemas, Tables in Exasol with Durable Subscription, Message headers and properties, Dead Letter Queue, Queue 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 Load CRM and ERP records into Exasol tables on a schedule so analysts query fresh operational data.
  • 02 Sync computed metrics or customer segments from Exasol back into a CRM for sales and marketing use (reverse ETL).
  • 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

Backfill history, then stay live

Load the existing set of Durable Subscription, Message headers and properties, Dead Letter Queue, Queue into Exasol 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 Exasol 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.

Exasol objects Jms objects How this pairing syncs
Tables Primary sync target; columnar relational tables written with standard SQL. BytesMessage Raw binary body for files, protobuf, or opaque payloads; passed through as a byte stream when structured field mapping is not required. Tables is specific to Exasol and BytesMessage to Jms — each maps to any object or custom field on the other side.
Views Read-only query surfaces often used as curated sources for reverse ETL. 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. Views is specific to Exasol and Durable Subscription to Jms — each maps to any object or custom field on the other side.
Virtual schemas Federated views over external sources; useful for deciding what needs physical replication. Message headers and properties JMSCorrelationID, JMSReplyTo, JMSTimestamp, JMSType plus JMSX/application-defined properties; used for correlation, routing, and selector-based filtering. Virtual schemas is specific to Exasol and Message headers and properties to Jms — each maps to any object or custom field on the other side.
UDF scripts In-database functions that can transform synced data after load. 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. UDF scripts is specific to Exasol and Dead Letter Queue to Jms — each maps to any object or custom field on the other side.
Users and roles Grant read/write access for the dedicated integration account. 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. Users and roles is specific to Exasol and Queue to Jms — each maps to any object or custom field on the other side.
Schemas Namespaces that group the tables a sync reads from or writes into. 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. Schemas is specific to Exasol and Topic to Jms — each maps to any object or custom field on the other side.

How changes propagate between Exasol 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.

Exasol Jms Interval-based propagation

DetectionStacksync polls Exasol for changes on an incremental schedule, reading only records changed since the previous pass. Polling with timestamp or key columns.

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

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

Rate-limit considerations

  • Exasol: No API quota; concurrency is bounded by cluster resources and session limits.
  • 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 Exasol ⇄ Jms

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Exasol 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 Exasol or Jms record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Exasol and Jms connectors work

Exasol

Integration surface
SQL over JDBC/ODBC drivers and a WebSocket-based client protocol
Authentication
Database credentials (username and password)
Change detection
Polling with timestamp or key columns; Exasol does not expose a transaction-log change feed to clients
Capabilities
read · write
Rate limits
No API quota; concurrency is bounded by cluster resources and session limits

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 Exasol 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 Exasol 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
    Exasol connected
    Jms connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Exasol 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.

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 311 integrations available for Exasol and Jms.

Popular · 6 of 311
All Exasol integrations All Jms 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