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Database ⇄ Data warehouse

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

Keep Apache Cassandra and Materialize 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

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Why teams connect Apache Cassandra and Materialize

Connect Apache Cassandra and Materialize with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want Apache Cassandra's rows in Materialize, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Apache Cassandra where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Apache Cassandra sync into Materialize in real time, and result tables in Materialize sync back into Apache Cassandra, with schema and type mapping between the two systems handled for you.

Common use cases

  • Drive alerting and operational tooling from SUBSCRIBE change streams instead of scheduled queries.
  • Maintain real-time inventory, usage, or account-health counters consumed by customer-facing applications.
  • Sync customer profile data between Cassandra and a CRM so operational apps and sales tools agree.
  • Write attributes computed elsewhere (scores, preferences) back into Cassandra tables serving low-latency reads.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

Offload heavy reads

Point analytical queries at the synced copy in Materialize and keep Apache Cassandra focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from Apache Cassandra land in Materialize as they change, replacing hand-built CDC and batch extract jobs.

What you can sync between Apache Cassandra and Materialize

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 Materialize objects
Materialized Views Server-maintained denormalized views; considered experimental and disabled by default in recent releases. Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize.
Secondary Indexes Optional indexes that allow filtered reads outside the partition key. Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets.
User-Defined Types Composite column types that syncs must flatten or map to structured fields. Sinks Outbound connections that emit view changes to Kafka topics.
Collections List, set, and map columns handled with type-aware field mapping. Indexes In-memory arrangements that make view reads fast for serving workloads.
Counters Increment-only counter columns, usually read-only in syncs. Clusters Compute pools that isolate ingestion, view maintenance, and serving.
Keyspaces Top-level namespaces with replication settings that scope a sync connection. Connections & Secrets Stored credentials and endpoints used by sources and sinks.
What ships with Apache Cassandra ⇄ Materialize

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Cassandra or Materialize 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 Materialize record.

Observability

Monitoring

Track your Apache Cassandra ⇄ Materialize 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 Materialize.

How the Apache Cassandra and Materialize 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

Materialize

Integration surface
PostgreSQL wire protocol (SQL)
Authentication
Database credentials (username/password; app passwords in the managed cloud service)
Change detection
SUBSCRIBE queries stream row-level changes of any view or table to the client
Capabilities
read · write · CDC
How it works

How to connect Apache Cassandra to Materialize — 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 Materialize 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
    Materialize connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Apache Cassandra and Materialize integration FAQ

SECURITY

Security teams love 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
CSA STAR
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 386 integrations available for Apache Cassandra and Materialize.

Popular · 8 of 386
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