# Analytics

## MariaDB ColumnStore

For fast, ad hoc analytics at scale, MariaDB ColumnStore is a powerful columnar database that can be deployed as a standalone analytics solution or integrated with MariaDB Enterprise Server to act as a powerful query accelerator. It stores data in a columnar format and can be distributed across a cluster of servers, allowing it to execute complex queries in parallel on petabytes of data.

This integration allows you to access your InnoDB data in near-real time, processing it directly in the ColumnStore engine to run fast, parallel OLAP queries straight from your transactional data. This eliminates the need to maintain a separate pipeline or use delayed batch inserts to analyze your live data.

{% content-ref url="/pages/k39rPindnT83pKuTooef" %}
[MariaDB ColumnStore](/docs/analytics/mariadb-columnstore.md)
{% endcontent-ref %}

## MariaDB Exa

For the ultimate in analytical performance, the joint solution between MariaDB and Exasol connects your mission-critical transactional data to the world’s fastest analytics engine. Available on-premise or in the cloud on platforms like AWS and Microsoft Azure, this solution brings high-speed analytics to any environment.

MariaDB Exa erases the barrier between live operational data and high-speed analytics, leveraging Exasol’s massively parallel processing (MPP) and in-memory engine. It is the ideal solution for powering your most demanding analytics and AI/ML workloads with unmatched speed and efficiency.

{% content-ref url="/pages/US0rSIAicOWV7vU8JfNW" %}
[MariaDB Exa](/docs/analytics/mariadb-exa.md)
{% endcontent-ref %}

<sub>*This page is: Copyright © 2025 MariaDB. All rights reserved.*</sub>

{% @marketo/form formId="4316" %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://mariadb.com/docs/analytics/readme.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
