Two-way sync
Changes in Apache Cassandra or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Cassandra and TimescaleDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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 TimescaleDB 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.
Keep the same dataset live in both Apache Cassandra and TimescaleDB, so each workload runs on the engine that suits it.
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
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 | TimescaleDB objects | |
|---|---|---|
| Partitions and Rows Records located by partition and clustering keys during reads and upserts. | Schemas Postgres namespaces used to separate synced datasets by team or environment. | |
| Materialized Views Server-maintained denormalized views; considered experimental and disabled by default in recent releases. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | |
| Secondary Indexes Optional indexes that allow filtered reads outside the partition key. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. | |
| User-Defined Types Composite column types that syncs must flatten or map to structured fields. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | |
| Collections List, set, and map columns handled with type-aware field mapping. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. | |
| Counters Increment-only counter columns, usually read-only in syncs. | Views Standard SQL views used to shape or filter data for consumers. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Cassandra–TimescaleDB connection.
Changes in Apache Cassandra or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Cassandra or TimescaleDB data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Cassandra or TimescaleDB record.
Track your Apache Cassandra ⇄ TimescaleDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Cassandra and TimescaleDB.
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.
Authenticate Apache Cassandra and TimescaleDB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Apache Cassandra and TimescaleDB 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Apache Cassandra and TimescaleDB: authenticate both systems, choose the objects to sync (such as Apache Cassandra's Partitions and Rows and Materialized Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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 TimescaleDB records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Cassandra and TimescaleDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Cassandra–TimescaleDB integration in-house.
Yes — Stacksync ships production-grade connectors for both Apache Cassandra and TimescaleDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Apache Cassandra: Commit-log based CDC on tables with CDC enabled, or polling using writetime metadata and timestamp columns. On TimescaleDB: Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Apache Cassandra side: Collections, Counters, Keyspaces, Tables, plus custom fields where Apache Cassandra exposes them. On the TimescaleDB side: Schemas, Hypertables, Chunks, Continuous Aggregates. Stacksync auto-detects both schemas and converts types between the two systems.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Apache Cassandra and TimescaleDB.