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Database ⇄ Data warehouse

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

Keep Apache Cassandra and ClickHouse 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 ClickHouse

Connect Apache Cassandra and ClickHouse 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 ClickHouse, 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 ClickHouse in real time, and result tables in ClickHouse sync back into Apache Cassandra, with schema and type mapping between the two systems handled for you.

Common use cases

  • 01 Sync aggregated ClickHouse query results back into operational tools, such as account-level usage metrics into a CRM.
  • 02 Consolidate logs and business records from multiple sources into MergeTree tables for retention and reporting.
  • 03 Consolidate data from multiple keyspaces or clusters into one reporting store.
  • 04 Replicate high-volume event or profile tables from Cassandra into a warehouse for analytics that CQL cannot express.

Common sync patterns

Serve warehouse results at database speed

Aggregates or model outputs computed in ClickHouse sync into Apache Cassandra, where whatever reads from that database gets them without querying the warehouse.

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 ClickHouse and keep Apache Cassandra focused on its operational workload.

What you can sync between Apache Cassandra and ClickHouse

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 ClickHouse objects How this pairing syncs
Materialized Views Server-maintained denormalized views; considered experimental and disabled by default in recent releases. Materialized views Insert-time transformations that reshape incoming synced rows into aggregates. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Tables Wide-column tables addressed by partition key, the unit of row-level sync. Distributed tables Query-routing tables over cluster shards in self-managed deployments. Tables is specific to Apache Cassandra and Distributed tables to ClickHouse — 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. Dictionaries In-memory lookup structures refreshed from external sources, sometimes fed by syncs. Partitions and Rows is specific to Apache Cassandra and Dictionaries to ClickHouse — each maps to any object or custom field on the other side.
Secondary Indexes Optional indexes that allow filtered reads outside the partition key. Tables (MergeTree family) Columnar, append-optimized tables that serve as the destination for high-volume sync loads. Secondary Indexes is specific to Apache Cassandra and Tables (MergeTree family) to ClickHouse — each maps to any object or custom field on the other side.
User-Defined Types Composite column types that syncs must flatten or map to structured fields. Databases Namespaces that group tables and scope permissions for sync users. User-Defined Types is specific to Apache Cassandra and Databases to ClickHouse — each maps to any object or custom field on the other side.
Collections List, set, and map columns handled with type-aware field mapping. Views Saved queries used as curated, read-only sync sources. Collections is specific to Apache Cassandra and Views to ClickHouse — each maps to any object or custom field on the other side.

How changes propagate between Apache Cassandra and ClickHouse

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 ClickHouse 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 applied to ClickHouse as a row-level write, with types converted between the two schemas.

ClickHouse Apache Cassandra Interval-based propagation

DetectionStacksync polls ClickHouse for changes on an incremental schedule, reading only records changed since the previous pass. No log-based CDC for consumers.

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.
What ships with Apache Cassandra ⇄ ClickHouse

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Cassandra or ClickHouse 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 ClickHouse record.

Observability

Monitoring

Track your Apache Cassandra ⇄ ClickHouse 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 ClickHouse.

How the Apache Cassandra and ClickHouse 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

ClickHouse

Integration surface
Native TCP protocol and HTTP interface; standard SQL dialect, with MySQL and PostgreSQL wire compatibility available
Authentication
Database credentials (username/password); ClickHouse Cloud issues per-service credentials over TLS
Change detection
No log-based CDC for consumers; incremental reads use polling on monotonic columns, and ClickHouse is usually the destination rather than the source
Capabilities
read · write
How it works

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

    Choose tables

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

Apache Cassandra and ClickHouse 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 464 integrations available for Apache Cassandra and ClickHouse.

Popular · 5 of 464
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