Two-way sync
Changes in Amazon Redshift or MariaDB instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon Redshift 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.
Operational databases and analytical warehouses want the same data at different moments. Analysts want MariaDB'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 MariaDB where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in MariaDB sync into Amazon Redshift in real time, and result tables in Amazon Redshift sync back into MariaDB, with schema and type mapping between the two systems handled for you.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Point analytical queries at the synced copy in Amazon Redshift and keep MariaDB focused on its operational workload.
Rows from MariaDB land in Amazon Redshift as they change, replacing hand-built CDC and batch extract jobs.
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 | MariaDB objects | How this pairing syncs | |
|---|---|---|---|
| Tables Columnar tables used as sync destinations for SaaS and database data. | 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. | |
| Views SQL views readable as modeled sources for reverse syncs. | Views Read-side projections used as outbound sync sources. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Stored Procedures SQL procedures sometimes invoked around load steps. | Stored Procedures Server-side logic that can post-process synced rows. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| External Tables (Spectrum) S3-backed tables queryable through Redshift, readable in syncs. | Columns Field-level mapping targets with engine-typed values. | External Tables (Spectrum) is specific to Amazon Redshift and Columns to MariaDB — each maps to any object or custom field on the other side. | |
| Users and Groups Principals used to grant a sync connection scoped access. | Primary and Unique Keys Match keys for idempotent upserts. | Users and Groups is specific to Amazon Redshift and Primary and Unique Keys to MariaDB — each maps to any object or custom field on the other side. | |
| Databases Top-level containers within a cluster or serverless workgroup. | System-Versioned Tables Temporal tables that retain row history natively, useful for auditing synced changes. | Databases is specific to Amazon Redshift and System-Versioned Tables 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.
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 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 applied to Amazon Redshift as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Redshift–MariaDB connection.
Changes in Amazon Redshift or MariaDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon Redshift 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 Amazon Redshift or MariaDB record.
Track your Amazon Redshift ⇄ MariaDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon Redshift 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 Amazon Redshift 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 Amazon Redshift 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 Amazon Redshift and MariaDB: authenticate both systems, choose the objects to sync (such as Amazon Redshift's Tables and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Amazon Redshift: Polling or query-based diffing; Redshift does not expose a transaction log for external CDC consumers. 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 Amazon Redshift side: Stored Procedures, Users and Groups, Databases, Schemas, plus custom fields where Amazon Redshift exposes them. On the MariaDB side: System-Versioned Tables, JSON Columns, Stored Procedures, Databases (Schemas). 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 Amazon Redshift and MariaDB: Fresh analytics without loading windows; Offload heavy reads; Operational data in the warehouse, minus the pipeline. Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Amazon Redshift: SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS. Authentication: Database credentials or IAM-based authentication. MariaDB: SQL wire protocol (MySQL-compatible client/server protocol). Authentication: Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host). Stacksync manages authentication, retries, and rate limits on both sides.
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 479 integrations available for Amazon Redshift and MariaDB.