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Jms to Redis Enterprise integration — real-time, two-way sync

Keep Jms and Redis Enterprise 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 Jms and Redis Enterprise

Keep Redis Enterprise and Jms in step: the rows in your database and the Queue, Topic, TextMessage, MapMessage your engineering tools track stay consistent in real time, in both directions.

Redis Enterprise is where your application's durable data lives; Jms 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 Pub/Sub channels, Search indexes, Keys (Strings), Hashes in Redis Enterprise 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 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 Write counters and leaderboard state from sorted sets back to an operational database for durable reporting.
  • 02 Cache CRM or ERP records into Redis hashes so applications read customer data with sub-millisecond in-memory latency instead of hitting SaaS APIs.
  • 03 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.
  • 04 Fan out inventory or pricing updates onto a Topic with durable subscriptions so multiple services stay aligned even after downtime.

Common sync patterns

React to changes on either side in near real time

Updates in Jms arrive as row changes in Redis Enterprise, and writes to Redis Enterprise propagate to Jms within seconds, so triggers, jobs, and alerts fire without polling.

Where Jms manages users or groups: keep identity aligned

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

Turn rows into the records your tools track

A new or changed row in Redis Enterprise creates or updates the matching record in Jms, whether that is an issue, an event, a message, or a user, so the tool reflects the database without a custom API job.

What you can sync between Jms and Redis Enterprise

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 Redis Enterprise objects How this pairing syncs
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. Streams Append-only logs with consumer groups, used to fan sync events out to downstream services. Queue is specific to Jms and Streams to Redis Enterprise — each maps to any object or custom field on the other side.
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. Pub/Sub channels Fire-and-forget messaging used to notify applications when synced keys change. Topic is specific to Jms and Pub/Sub channels to Redis Enterprise — each maps to any object or custom field on the other side.
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. Search indexes Secondary indexes (RediSearch) that make synced hashes and JSON documents queryable. TextMessage is specific to Jms and Search indexes to Redis Enterprise — 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. Keys (Strings) Simple key-value pairs used to cache individual synced records or lookup values. MapMessage is specific to Jms and Keys (Strings) to Redis Enterprise — 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. Hashes Field-value maps that commonly hold one synced row per hash, keyed by record ID. BytesMessage is specific to Jms and Hashes to Redis Enterprise — 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. JSON documents Native JSON storage (RedisJSON) for nested records synced from APIs or document stores. Durable Subscription is specific to Jms and JSON documents to Redis Enterprise — each maps to any object or custom field on the other side.

How changes propagate between Jms and Redis Enterprise

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

Redis Enterprise Jms Interval-based propagation

DetectionStacksync polls Redis Enterprise for changes on an incremental schedule, reading only records changed since the previous pass. Keyspace notifications over pub/sub or reads from Redis Streams.

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.).
  • Redis Enterprise: Throughput is bounded by provisioned cluster capacity rather than published API rate limits.
What ships with Jms ⇄ Redis Enterprise

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Jms or Redis Enterprise 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 Redis Enterprise record.

Observability

Monitoring

Track your Jms ⇄ Redis Enterprise 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 Redis Enterprise.

How the Jms and Redis Enterprise 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.).

Redis Enterprise

Integration surface
Redis wire protocol (RESP) via client libraries; separate REST API for cluster management
Authentication
Password or ACL-based credentials, typically over TLS
Change detection
Keyspace notifications over pub/sub or reads from Redis Streams; no transaction-log CDC surface for data
Capabilities
read · write
Rate limits
Throughput is bounded by provisioned cluster capacity rather than published API rate limits
How it works

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

    Choose tables

    Pick the Jms and Redis Enterprise 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 ⇄ Redis Enterprise
    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 Redis Enterprise
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Jms and Redis Enterprise 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 313 integrations available for Jms and Redis Enterprise.

Popular · 7 of 313
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