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Database ⇄ Data warehouse

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

Keep Apache Cassandra and Firebolt 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 Apache Cassandra and Firebolt

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

Common use cases

  • 01 Sync CRM objects into Firebolt so customer-facing dashboards reflect recent pipeline changes.
  • 02 Keep dimension tables aligned with source systems while high-volume event data loads through separate batch pipelines.
  • 03 Sync customer profile data between Cassandra and a CRM so operational apps and sales tools agree.
  • 04 Write attributes computed elsewhere (scores, preferences) back into Cassandra tables serving low-latency reads.

Common sync patterns

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 Firebolt and keep Apache Cassandra focused on its operational workload.

Operational data in the warehouse, minus the pipeline

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

What you can sync between Apache Cassandra and Firebolt

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 Firebolt objects How this pairing syncs
Tables Wide-column tables addressed by partition key, the unit of row-level sync. Tables Managed columnar tables written with SQL; the main sync destination. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Collections List, set, and map columns handled with type-aware field mapping. External tables References to files in object storage used to stage bulk loads. Collections is specific to Apache Cassandra and External tables to Firebolt — each maps to any object or custom field on the other side.
Counters Increment-only counter columns, usually read-only in syncs. Views Curated query surfaces commonly used as sources for reverse ETL. Counters is specific to Apache Cassandra and Views to Firebolt — each maps to any object or custom field on the other side.
Keyspaces Top-level namespaces with replication settings that scope a sync connection. Aggregating indexes Precomputed rollups maintained at write time; incremental loads update them automatically. Keyspaces is specific to Apache Cassandra and Aggregating indexes to Firebolt — 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. Engines Compute resources that must be running for a sync to read or write. Partitions and Rows is specific to Apache Cassandra and Engines to Firebolt — 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. Databases Logical containers holding the tables a sync targets. Materialized Views is specific to Apache Cassandra and Databases to Firebolt — each maps to any object or custom field on the other side.

How changes propagate between Apache Cassandra and Firebolt

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

Firebolt Apache Cassandra Interval-based propagation

DetectionStacksync polls Firebolt for changes on an incremental schedule, reading only records changed since the previous pass. 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.
  • Firebolt: No fixed request quota; throughput depends on the engine size attached to the workload.
What ships with Apache Cassandra ⇄ Firebolt

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Cassandra or Firebolt 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 Firebolt record.

Observability

Monitoring

Track your Apache Cassandra ⇄ Firebolt 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 Firebolt.

How the Apache Cassandra and Firebolt 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

Firebolt

Integration surface
SQL over a REST API, with JDBC, Python, and Node.js SDKs
Authentication
Service account credentials (client ID and secret) exchanged for OAuth 2.0 tokens
Change detection
Polling; Firebolt is an analytics destination and does not expose a change feed
Capabilities
read · write
Rate limits
No fixed request quota; throughput depends on the engine size attached to the workload
How it works

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

    Choose tables

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

Apache Cassandra and Firebolt 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 365 integrations available for Apache Cassandra and Firebolt.

Popular · 3 of 365
All Apache Cassandra integrations All Firebolt integrations Browse all integrations
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