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MariaDB

MariaDB Enterprise Server Q2 2026 Maintenance Releases | MariaDB MariaDB R2DBC Connector 1.4.1 now available | MariaDB MariaDB Java Connector 3.5.9, 3.4.3, 3.3.5, and 2.7.14 now available | MariaDB MariaDB Connector/C 3.4.9, and 3.3.19 now available | MariaDB MariaDB Node.js Connector 3.5.3 and 3.4.6 now available | MariaDB Comprehensive Self-Service Backups for Continuous Data Protection in MariaDB Cloud | MariaDB MariaDB Enterprise Server Q1 2026 Corrective Releases | MariaDB MariaDB Community Server 12.3 LTS: How It Scales AI Workloads and Delivers 4x Write Performance | MariaDB MariaDB Community Server Q2 2026 corrective releases | MariaDB How MariaDB Cloud Optimizes Database Resilience and Cost: A Deep Dive into High Availability | MariaDB Stop Paying for Air: Most Cloud Database Spend Is Wasted | MariaDB MariaDB Community Server Q2 2026 maintenance releases | MariaDB MariaDB Community Server 10.6 Is Reaching End of Life – Here’s What to Do Next | MariaDB A Clearer Path Forward for GridGain Customers | MariaDB We ran an internal AI demo competition: Here are the winners! | MariaDB MariaDB Java Connector 3.5.8 now available | MariaDB What’s New in MariaDB AI RAG 1.1: Ingestion, Reranking, and Docker Deployment | MariaDB
High Performance Real-Time Analytics on MariaDB Cloud: MariaDB Exa Technical Preview | MariaDB
https://www.facebook.com/MariaDB.dbms · 2026-06-16 · via MariaDB

Key takeaways

  • Analyze live data up to 800x faster by running high-performance analytics directly on your transactional database without the hassle or delays of building complex ETL pipelines.
  • Keep your existing application code exactly as it is while intelligent routing automatically directs transactional and analytical queries to the right engine behind the scenes.
  • Get up and running in minutes with a fully managed cloud service that eliminates operational complexity, giving your team instant access to fresh data for real-time insights and AI modeling.

We are excited to announce the technical preview of MariaDB Exa on MariaDB Cloud. This release brings high-performance Hybrid Transactional and Analytical Processing (HTAP) directly into the MariaDB environment by integrating Exasol’s massively parallel processing (MPP) engine. By removing the requirement for complex ETL pipelines, MariaDB Exa enables analytics on live transactional data at up to 800x the speed of traditional configurations.

Delivering MariaDB Exa as a managed cloud service removes the operational complexity that typically gates HTAP adoption. There are no clusters to provision, no MaxScale routing to configure, and no replication topology to maintain. Provisioning is a single workflow inside MariaDB Cloud, with MaxScale automatically handling the intelligent routing between the transactional and analytical engines. This lets you validate the HTAP value proposition against real workloads in minutes rather than days, in a single managed environment that grows with you as workloads evolve.

The same extreme analytics experience is available whether you run MariaDB Exa yourself or consume it as a Cloud-managed service. Both transactional and analytical power, on-prem or in-cloud, with no architectural compromise between the two. That’s a deployment flexibility that pure cloud-only warehouses can’t match.

MariaDB Exa Eliminates ETL Complexity

Traditional data pipelines create significant operational overhead. They introduce complexity, increase cloud egress costs, and create data drift. MariaDB Exa on MariaDB Cloud removes these barriers by providing a single, unified interface for both OLTP and OLAP workloads.

  • Fully Managed Infrastructure: Organizations access the capabilities of an MPP columnar database within a fully managed cloud ecosystem, eliminating manual database provisioning and maintenance.
  • Removal of Brittle Pipelines: Analytics run on live transactional data without the lag or overhead of batch ETL jobs.
  • High-Concurrency Execution: Unlike hyperscaler cloud databases that throttle under heavy analytical concurrency, the Exa engine processes simultaneous, complex queries over massive datasets without latency.

MariaDB MaxScale Ensures Intelligent Query Routing

The core of this architecture is MariaDB MaxScale, which acts as an intelligent backend proxy for both transactional and analytical workloads. Database connection strings and application logic remain unchanged; applications point directly to MaxScale, which handles query routing transparently.

MariaDB MaxScale with Exa Architecture

MaxScale evaluates every incoming SQL statement to optimize execution:

Operation TypeRouting DestinationBenefit
Write OperationsMariaDBEnsures strict ACID compliance and data consistency.
Read-after-writeMariaDBMaintains immediate data accuracy.
Analytical QueriesMariaDB Exa (Exasol MPP Engine)Processes complex scans, joins, and aggregations with massive parallelism.

In advanced routing scenarios, MaxScale dispatches queries to both engines simultaneously. It returns the fastest successful response to the client, terminates the slower process, and caches the query metadata to optimize routing paths for future executions.

Change Data Capture Maintains Data Consistency

To preserve data consistency without manual intervention, MariaDB Exa utilizes a native Change Data Capture (CDC) pipeline. This pipeline monitors MariaDB binary logs and immediately streams transactional changes—inserts, updates, and deletes—directly into the synchronized Exasol replica. This background process ensures analytical queries execute against current production data without impacting the transactional engine’s throughput.

Enterprise Use Cases for MariaDB Exa

MariaDB Exa is engineered for organizations that can no longer afford the delay between transactions and insights.

Real-time business analytics

Organizations in high-velocity sectors like finance, e-commerce, and logistics require immediate insights to prevent revenue loss. Powered by Exasol’s MPP engine, MariaDB Exa delivers near real-time analytic insights directly from live operational data.

Modern AI & machine learning

AI models depend on data freshness. Training and inference on outdated datasets lead to missed patterns and erroneous predictions. With MariaDB Exa, models are trained and deployed directly against live operational data. Exasol’s integrated AI/ML execution framework enables organizations to score transactions, detect anomalies, and optimize operations in real-time.

Operational Benefits by Role

  • DBAs & DevOps: Eliminate the maintenance of external analytics connectors and reduce the storage footprint of redundant data copies.
  • Enterprise Architects: Simplify the data architecture where one platform handles the full lifecycle of data from ingestion to deep analytics.
  • Application Developers: Build real-time features, such as fraud detection or live inventory reordering, without worrying about query performance bottlenecks.
  • Data Scientists: Access live production data for real-time model inference rather than working off stale, offline exports.

Conclusion and Next Steps

MariaDB Exa bridges the gap between transactional reliability and analytical speed. By integrating Exasol’s MPP engine into the MariaDB Cloud platform, organizations can modernize their data architecture, reduce operational complexity, and unlock real-time insights from operational data.

Join the Technical Preview

The MariaDB Exa Technical Preview is open to all MariaDB Cloud users running provisioned instances. Organizations can deploy a test environment today to run complex analytical queries directly against live transactional data and evaluate performance improvements firsthand.

Frequently Asked Questions

MariaDB Exa combines MariaDB’s transactional OLTP engine with Exasol’s MPP analytical engine in a single, managed platform. This integration allows organizations to execute hybrid transactional and analytical processing (HTAP) queries without needing complex ETL pipelines, ensuring that analytical workloads run against live production data.

MariaDB MaxScale acts as an intelligent proxy that analyzes incoming SQL statements. It automatically routes transactional writes and reads to MariaDB for ACID compliance, while complex analytical queries—such as multi-way joins and aggregations—are routed to the Exasol MPP engine, all without requiring changes to application connection strings.

MariaDB Exa uses a native Change Data Capture (CDC) pipeline. This process monitors MariaDB binary logs and streams transactional changes—such as inserts, updates, and deletes—into the Exasol replica in real-time. This ensures that analytical queries execute against current data without impacting the performance of the transactional database.

Yes. MariaDB Exa allows data scientists to train and deploy AI models directly against live operational data. Because Exasol’s engine supports high-performance analytical execution, organizations can perform real-time anomaly detection, transaction scoring, and predictive modeling without waiting for nightly batch processing or relying on outdated data extracts.