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Data warehouse ⇄ Database

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

Keep Amazon Redshift and Apache Cassandra 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 Amazon Redshift and Apache Cassandra

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

Common use cases

  • 01 Centralize CRM, ERP, and product data in Redshift so analysts join it with warehouse tables.
  • 02 Publish finance rollups computed in Redshift back to spreadsheets or operational tools.
  • 03 Feed Cassandra change streams into search indexes or caches that must track the source of truth.
  • 04 Consolidate data from multiple keyspaces or clusters into one reporting store.

Common sync patterns

Offload heavy reads

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

Operational data in the warehouse, minus the pipeline

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

Serve warehouse results at database speed

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

What you can sync between Amazon Redshift and Apache Cassandra

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.

Amazon Redshift objects Apache Cassandra objects How this pairing syncs
Tables Columnar tables used as sync destinations for SaaS and database data. Tables Wide-column tables addressed by partition key, the unit of row-level sync. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Materialized Views Precomputed results that downstream syncs can read for performance. Materialized Views Server-maintained denormalized views; considered experimental and disabled by default in recent releases. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Schemas Namespaces used to organize synced tables and control grants. Keyspaces Top-level namespaces with replication settings that scope a sync connection. Schemas is specific to Amazon Redshift and Keyspaces to Apache Cassandra — each maps to any object or custom field on the other side.
Views SQL views readable as modeled sources for reverse syncs. Partitions and Rows Records located by partition and clustering keys during reads and upserts. Views is specific to Amazon Redshift and Partitions and Rows to Apache Cassandra — each maps to any object or custom field on the other side.
External Tables (Spectrum) S3-backed tables queryable through Redshift, readable in syncs. Secondary Indexes Optional indexes that allow filtered reads outside the partition key. External Tables (Spectrum) is specific to Amazon Redshift and Secondary Indexes to Apache Cassandra — each maps to any object or custom field on the other side.
Stored Procedures SQL procedures sometimes invoked around load steps. User-Defined Types Composite column types that syncs must flatten or map to structured fields. Stored Procedures is specific to Amazon Redshift and User-Defined Types to Apache Cassandra — each maps to any object or custom field on the other side.

How changes propagate between Amazon Redshift and Apache Cassandra

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.

Amazon Redshift Apache Cassandra Interval-based propagation

DetectionStacksync polls Amazon Redshift for changes on an incremental schedule, reading only records changed since the previous pass. Polling or query-based diffing.

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

Apache Cassandra Amazon Redshift 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 Amazon Redshift as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Amazon Redshift: Bounded by cluster or serverless capacity and concurrency settings rather than API quotas.
  • Apache Cassandra: No API quotas; throughput is governed by cluster capacity and consistency-level choices.
What ships with Amazon Redshift ⇄ Apache Cassandra

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Redshift or Apache Cassandra 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 Amazon Redshift or Apache Cassandra record.

Observability

Monitoring

Track your Amazon Redshift ⇄ Apache Cassandra sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon Redshift and Apache Cassandra.

How the Amazon Redshift and Apache Cassandra connectors work

Amazon Redshift

Integration surface
SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS
Authentication
Database credentials or IAM-based authentication
Change detection
Polling or query-based diffing; Redshift does not expose a transaction log for external CDC consumers
Capabilities
read · write
Rate limits
Bounded by cluster or serverless capacity and concurrency settings rather than API quotas

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
How it works

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

    Choose tables

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

Amazon Redshift and Apache Cassandra 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
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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 466 integrations available for Amazon Redshift and Apache Cassandra.

Popular · 5 of 466
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