Real-time
Two-way sync
Changes in Apache Cassandra or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Database
Apache Cassandra to Postgres Heroku integration — real-time, two-way sync
Keep Apache Cassandra and Postgres Heroku 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
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Apache Cassandra and Postgres Heroku
Keep Apache Cassandra and Postgres Heroku synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between Apache Cassandra and Postgres Heroku continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- 01 Write attributes computed elsewhere (scores, preferences) back into Cassandra tables serving low-latency reads.
- 02 Feed Cassandra change streams into search indexes or caches that must track the source of truth.
- 03 Expose CRM objects as Postgres tables the Heroku application can query and join directly
- 04 Sync Heroku Postgres into a warehouse for reporting without running ETL dynos
Common sync patterns
Cross-engine sync
Keep the same dataset live in both Apache Cassandra and Postgres Heroku, so each workload runs on the engine that suits it.
Migration with zero-downtime cutover
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
What you can sync between Apache Cassandra and Postgres Heroku
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 | Postgres Heroku objects | How this pairing syncs | |
|---|---|---|---|
| Tables Wide-column tables addressed by partition key, the unit of row-level sync. | Tables Standard Postgres tables; the primary two-way sync target for app data. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Materialized Views Server-maintained denormalized views; considered experimental and disabled by default in recent releases. | Materialized Views Precomputed result sets synced outward on refresh. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Secondary Indexes Optional indexes that allow filtered reads outside the partition key. | Schemas Namespaces that scope which tables a sync reads and writes. | Secondary Indexes is specific to Apache Cassandra and Schemas to Postgres Heroku — 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. | Primary and Unique Keys Match keys for idempotent upserts from connected systems. | User-Defined Types is specific to Apache Cassandra and Primary and Unique Keys to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Collections List, set, and map columns handled with type-aware field mapping. | JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. | Collections is specific to Apache Cassandra and JSONB Columns to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Counters Increment-only counter columns, usually read-only in syncs. | Sequences Generate surrogate keys for rows created by inbound syncs. | Counters is specific to Apache Cassandra and Sequences to Postgres Heroku — each maps to any object or custom field on the other side. |
How changes propagate between Apache Cassandra and Postgres Heroku
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 Postgres Heroku 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 Postgres Heroku as a row-level write, with types converted between the two schemas.
Postgres Heroku Apache Cassandra Interval-based propagation
DetectionStacksync polls Postgres Heroku for changes on an incremental schedule, reading only records changed since the previous pass. Trigger-based capture or polling in most configurations.
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.
- Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
What ships with Apache Cassandra ⇄ Postgres Heroku
Connect Apache Cassandra and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Cassandra–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Apache Cassandra or Postgres Heroku 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 Postgres Heroku record.
Observability
Monitoring
Track your Apache Cassandra ⇄ Postgres Heroku 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 Postgres Heroku.
How the Apache Cassandra and Postgres Heroku 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
Postgres Heroku
- Integration surface
- SQL wire protocol (standard PostgreSQL)
- Authentication
- Database credentials from the Heroku DATABASE_URL config var; SSL required
- Change detection
- Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
- Capabilities
- read · write
- Rate limits
- No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
How it works
How to connect Apache Cassandra to Postgres Heroku — 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.
- 01
Connect your apps
Authenticate Apache Cassandra and Postgres Heroku with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Apache Cassandra
connected
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Apache Cassandra and Postgres Heroku 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.
objects · Apache Cassandra ⇄ Postgres HerokuCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Apache Cassandra Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Apache Cassandra and Postgres Heroku integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Apache Cassandra and Postgres Heroku: authenticate both systems, choose the objects to sync (such as Apache Cassandra's Tables and Materialized Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Apache Cassandra and Postgres Heroku: Cross-engine sync; Migration with zero-downtime cutover; Shared reference data between services. Keep the same dataset live in both Apache Cassandra and Postgres Heroku, so each workload runs on the engine that suits it.
-
Apache Cassandra: CQL over the Cassandra native binary protocol. Authentication: Database credentials (password authenticator); TLS and role-based grants where configured. Postgres Heroku: SQL wire protocol (standard PostgreSQL). Authentication: Database credentials from the Heroku DATABASE_URL config var; SSL required. Stacksync manages authentication, retries, and rate limits on both sides.
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Apache Cassandra: CDC is enabled per table and surfaces changes through commit-log segments, which is how log-based connectors consume Cassandra changes. Postgres Heroku: Heroku Postgres is standard PostgreSQL, so any Postgres client, driver, or SQL tool connects unchanged. Stacksync's field mapping accounts for these differences between Apache Cassandra and Postgres Heroku without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Apache Cassandra and Postgres Heroku records are not retained after a sync operation.
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.
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:
