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

Keep Apache Cassandra 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 Cassandra and Jms

Keep Apache Cassandra and Jms in step: the rows in your database and the MapMessage, BytesMessage, Durable Subscription, Message headers and properties your engineering tools track stay consistent in real time, in both directions.

Apache Cassandra 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 Materialized Views, Secondary Indexes, User-Defined Types, Collections in Apache Cassandra with MapMessage, BytesMessage, Durable Subscription, Message headers and properties 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 Replicate high-volume event or profile tables from Cassandra into a warehouse for analytics that CQL cannot express.
  • 02 Sync customer profile data between Cassandra and a CRM so operational apps and sales tools agree.
  • 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

Turn rows into the records your tools track

A new or changed row in Apache Cassandra 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.

Land tool activity as queryable rows

Records and events from Jms arrive in Apache Cassandra as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.

One integration pattern instead of per-tool API code

Read and write the synced tables in Apache Cassandra and Stacksync keeps Jms current, replacing the auth, webhooks, rate limits, and retry logic you would otherwise maintain for each tool.

What you can sync between Apache Cassandra 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 Cassandra objects Jms objects How this pairing syncs
Collections List, set, and map columns handled with type-aware field mapping. MapMessage Body of typed name/value pairs that maps directly onto record fields, so no custom body parsing is needed on read or write. Collections is specific to Apache Cassandra and MapMessage to Jms — each maps to any object or custom field on the other side.
Counters Increment-only counter columns, usually read-only in syncs. BytesMessage Raw binary body for files, protobuf, or opaque payloads; passed through as a byte stream when structured field mapping is not required. Counters is specific to Apache Cassandra and BytesMessage to Jms — each maps to any object or custom field on the other side.
Keyspaces Top-level namespaces with replication settings that scope a sync connection. 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. Keyspaces is specific to Apache Cassandra and Durable Subscription to Jms — each maps to any object or custom field on the other side.
Tables Wide-column tables addressed by partition key, the unit of row-level sync. 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 Cassandra and Message headers and properties to Jms — each maps to any object or custom field on the other side.
Partitions and Rows Records located by partition and clustering keys during reads and upserts. 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. Partitions and Rows is specific to Apache Cassandra and Dead Letter Queue to Jms — each maps to any object or custom field on the other side.
Materialized Views Server-maintained denormalized views; considered experimental and disabled by default in recent releases. 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. Materialized Views is specific to Apache Cassandra and Queue to Jms — each maps to any object or custom field on the other side.

How changes propagate between Apache Cassandra 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 Cassandra Jms Sub-second propagation

DetectionChanges in Apache Cassandra are captured at the source via change data capture — no polling loop against its API. Commit-log based CDC on tables with CDC enabled, or polling using writetime metadata and timestamp columns.

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

Jms Apache Cassandra 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 written to Apache Cassandra through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Apache Cassandra: No API quotas; throughput is governed by cluster capacity and consistency-level choices.
  • 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 Cassandra ⇄ Jms

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Cassandra 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 Cassandra or Jms record.

Observability

Monitoring

Track your Apache Cassandra ⇄ 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 Cassandra and Jms.

How the Apache Cassandra and Jms connectors work

Apache Cassandra

Integration surface
CQL over the Cassandra native binary protocol
Authentication
Database credentials (password authenticator); TLS and role-based grants where configured
Change detection
Commit-log based CDC on tables with CDC enabled, or polling using writetime metadata and timestamp columns
Capabilities
read · write · CDC
Rate limits
No API quotas; throughput is governed by cluster capacity and consistency-level choices

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

    Choose tables

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

Apache Cassandra 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 309 integrations available for Apache Cassandra and Jms.

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