Two-way sync
Changes in Apache Cassandra or MariaDB instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Cassandra and MariaDB 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 MariaDB 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 MariaDB, 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 | MariaDB objects | How this pairing syncs | |
|---|---|---|---|
| Tables Wide-column tables addressed by partition key, the unit of row-level sync. | Tables The primary sync target; rows map to records in connected systems. | 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. | Stored Procedures Server-side logic that can post-process synced rows. | Collections is specific to Apache Cassandra and Stored Procedures to MariaDB — each maps to any object or custom field on the other side. | |
| Counters Increment-only counter columns, usually read-only in syncs. | Databases (Schemas) Top-level namespaces that scope a sync's reads and writes. | Counters is specific to Apache Cassandra and Databases (Schemas) to MariaDB — each maps to any object or custom field on the other side. | |
| Keyspaces Top-level namespaces with replication settings that scope a sync connection. | Views Read-side projections used as outbound sync sources. | Keyspaces is specific to Apache Cassandra and Views to MariaDB — 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. | Columns Field-level mapping targets with engine-typed values. | Partitions and Rows is specific to Apache Cassandra and Columns to MariaDB — 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. | Primary and Unique Keys Match keys for idempotent upserts. | Materialized Views is specific to Apache Cassandra and Primary and Unique Keys to MariaDB — each maps to any object or custom field on the other side. |
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.
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 MariaDB as a row-level write, with types converted between the two schemas.
DetectionChanges in MariaDB are captured at the source via change data capture — no polling loop against its API. Database triggers — Stacksync creates deterministic triggers for internal logging and syncing.
DeliveryEach detected change is written to Apache Cassandra through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Cassandra–MariaDB connection.
Changes in Apache Cassandra or MariaDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Cassandra or MariaDB 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 MariaDB record.
Track your Apache Cassandra ⇄ MariaDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Cassandra and MariaDB.
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 MariaDB 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 MariaDB 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 MariaDB: authenticate both systems, choose the objects to sync (such as Apache Cassandra's Tables and Collections), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both Apache Cassandra and MariaDB. 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 MariaDB: Database triggers — Stacksync creates deterministic triggers for internal logging and syncing. 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: Tables, Partitions and Rows, Materialized Views, Secondary Indexes, plus custom fields where Apache Cassandra exposes them. On the MariaDB side: Databases (Schemas), Tables, Views, Columns. Stacksync auto-detects both schemas and converts types between the two systems.
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.
Common patterns for Apache Cassandra and MariaDB: Cross-engine sync; Migration with zero-downtime cutover; Shared reference data between services. Keep the same dataset live in both Apache Cassandra and MariaDB, so each workload runs on the engine that suits it.
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 369 integrations available for Apache Cassandra and MariaDB.