Real-time
Two-way sync
Changes in Databricks or MariaDB instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Databricks to MariaDB integration — real-time, two-way sync
Keep Databricks 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.
- 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
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Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Databricks and MariaDB
Connect MariaDB and Databricks 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 MariaDB's rows in Databricks, 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 Databricks in real time, and result tables in Databricks sync back into MariaDB, with schema and type mapping between the two systems handled for you.
Common use cases
- Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
- Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
- Feed a warehouse continuously from MariaDB using binlog-based capture instead of scheduled dumps
- Keep several MariaDB instances aligned with one system of record across environments
Offload heavy reads
Point analytical queries at the synced copy in Databricks and keep MariaDB focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from MariaDB land in Databricks as they change, replacing hand-built CDC and batch extract jobs.
Serve warehouse results at database speed
Aggregates or model outputs computed in Databricks sync into MariaDB, where whatever reads from that database gets them without querying the warehouse.
What you can sync between Databricks and MariaDB
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.
| Databricks objects | MariaDB objects | |
|---|---|---|
| Views Curated read-only projections used as sync sources for downstream tools. | Tables The primary sync target; rows map to records in connected systems. | |
| Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Views Read-side projections used as outbound sync sources. | |
| Volumes Unity Catalog file storage used for staging bulk loads. | Columns Field-level mapping targets with engine-typed values. | |
| SQL Warehouses The compute endpoint a sync connects to for query execution. | Primary and Unique Keys Match keys for idempotent upserts. | |
| Change Data Feed Row-level change records on Delta tables that drive incremental reads. | System-Versioned Tables Temporal tables that retain row history natively, useful for auditing synced changes. | |
| Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | JSON Columns Semi-structured payloads validated with JSON functions. |
What ships with Databricks ⇄ MariaDB
Connect Databricks and MariaDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–MariaDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Databricks or MariaDB 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 Databricks or MariaDB record.
Observability
Monitoring
Track your Databricks ⇄ MariaDB sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Databricks and MariaDB.
How the Databricks and MariaDB connectors work
Databricks
- Integration surface
- SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
- Authentication
- Personal access tokens or OAuth machine-to-machine credentials for service principals
- Change detection
- Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
- Capabilities
- read · write · CDC
- Rate limits
- Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits
MariaDB
- Integration surface
- 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)
- Change detection
- Database triggers — Stacksync creates deterministic triggers for internal logging and syncing
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput is bounded by connection limits and server resources
How it works
How to connect Databricks to MariaDB — 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 Databricks 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.
Databricks
connected
MariaDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Databricks 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.
objects · Databricks ⇄ MariaDBCustomers 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.
Databricks MariaDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Databricks and MariaDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Databricks and MariaDB: authenticate both systems, choose the objects to sync (such as Databricks's Views 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 Databricks and MariaDB: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Databricks and keep MariaDB focused on its operational workload.
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Databricks: SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution. Authentication: Personal access tokens or OAuth machine-to-machine credentials for service principals. 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.
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Databricks: Unity Catalog imposes a three-level namespace (catalog.schema.table) that governs access across workspaces. MariaDB: Composite primary keys are not supported (primary key must be a single column). Stacksync's field mapping accounts for these differences between Databricks and MariaDB 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 Databricks and MariaDB records are not retained after a sync operation.
SECURITY
Security teams love 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
CSA STAR
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Databricks and MariaDB.
Popular · 8 of 386
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Databricks ⇄ Firebase -
Databricks ⇄ SingleStore -
Databricks ⇄ Amazon Aurora -
Databricks ⇄ Amazon Lightsail -
MariaDB ⇄ Actian Vector - MariaDB ⇄ Amazon Redshift
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MariaDB ⇄ Apache Doris -
MariaDB ⇄ Apache Druid
No integrations match .
