Analytics and big data database

# ClickHouse analytical database

Deploy ClickHouse on Deplomo, an open-source columnar database for online analytical processing (OLAP) and reports on large datasets.

[Get started](https://panel.deplomo.com/signup)[Back to marketplace](/marketplace)

## Key benefits of deploying ClickHouse on Deplomo

Column-oriented analytics, persistent storage and a fixed monthly zone package.

### Columnar analytics

Columnar storage and parallel query execution help analyze large datasets. Performance depends on the data, query and available resources.

### Data compression

Built-in compression reduces disk usage and can help limit storage needs.

### SQL query support

Use SQL for queries, aggregations and statistical functions.

### OLAP and business intelligence

Use ClickHouse for analytical dashboards, log analysis, traffic statistics and large reporting workloads.

## ClickHouse FAQs

Answers to common questions about the ClickHouse columnar database:

What is ClickHouse, and how does it differ from a traditional relational database?

What are common uses for ClickHouse in big data systems?

What is the difference between OLTP and OLAP databases?

How do I connect ClickHouse to dashboard tools?

What should I consider when hosting ClickHouse in the cloud?

## ClickHouse guide: columnar storage and analytics for large datasets

As user activity, application events and system transactions accumulate, heavy analytical queries can affect operational databases. ClickHouse uses columnar storage and compression to support analytical aggregations over large datasets. Deploy it on Deplomo as a container and plan the resources your workload needs.

### What is ClickHouse, and what is different about its columnar architecture?

To understand ClickHouse, compare how databases store data. Row-oriented databases keep each record together, which suits individual transactions. ClickHouse stores each column separately, so an analytical query can read only the columns it needs. The performance difference depends on the query and dataset.

For business intelligence projects, connect ClickHouse to data tools such as [Metabase](/marketplace/apps/metabase) to build charts and explore data. To compare relational, NoSQL and in-memory databases, visit our [Cloud database](/products/databases) database guides.

### Manual ClickHouse setup compared with cloud deployment

Running ClickHouse on a traditional server can involve configuring XML files, ZooKeeper or ClickHouse Keeper for clusters, memory settings and storage paths. Misconfiguration can cause problems under heavy workloads.

Deplomo deploys ClickHouse in a container with platform storage and network settings. Configure resources for your workload and review the database setup before sending data.

### Compare ClickHouse on Deplomo with row-oriented databases and manual setup

The table compares ClickHouse with other database approaches:

<table class="w-full text-start text-sm"><thead class="border-b border-border/80 bg-muted/60 text-xs font-bold text-foreground"><tr><th class="p-4">Feature</th><th class="p-4 text-deplomo-600 dark:text-deplomo-400 font-extrabold">ClickHouse on Deplomo</th><th class="p-4">Traditional row-oriented databases (OLTP)</th><th class="p-4">Manual setup on a VPS</th></tr></thead><tbody class="divide-y divide-border/60 text-muted-foreground"><tr class="hover:bg-muted/30"><td class="p-4 font-semibold text-foreground">Aggregation query workload</td><td class="p-4 font-medium text-foreground">Designed for aggregations over large datasets</td><td class="p-4">May require additional planning for analytical workloads</td><td class="p-4">Performance depends on the workload and hardware configuration</td></tr><tr class="hover:bg-muted/30"><td class="p-4 font-semibold text-foreground">Data compression</td><td class="p-4 font-medium text-foreground">Columnar storage and compression can reduce disk usage; results depend on the data.</td><td class="p-4">May use more disk space for some workloads</td><td class="p-4">Compression settings require manual configuration</td></tr><tr class="hover:bg-muted/30"><td class="p-4 font-semibold text-foreground">Deployment and setup</td><td class="p-4 font-medium text-foreground">Deploy from a template</td><td class="p-4">Not designed for heavy analytical workloads</td><td class="p-4">Requires configuration of settings files and Keeper</td></tr><tr class="hover:bg-muted/30"><td class="p-4 font-semibold text-foreground">Pricing and resource scaling</td><td class="p-4 font-medium text-foreground">Fixed monthly EUR package pricing</td><td class="p-4">May require substantial hardware resources</td><td class="p-4">Fixed monthly fee with limited options to scale immediately</td></tr></tbody></table>

ClickHouse’s columnar storage and compression can help with analytical queries and disk use. Results depend on the workload and configuration.

### ClickHouse deployment and connection guide

Follow these steps to connect to ClickHouse:

- **Deploy from the marketplace** Open the Deplomo console and choose ClickHouse from the database apps.

- **Set RAM and NVMe storage** Choose resources based on the size of your analytical workload.

- **Find your connection details** When the service is ready, find the username, password and HTTP and native connection ports in the dashboard.

- **Connect and run queries** Use a graphical client such as DBeaver, or Python and Go libraries, to create MergeTree tables and analyze data.

### Deploy ClickHouse on Deplomo

ClickHouse is designed for analyzing large volumes of logs, events and business data. Choose resources and storage based on your workload, and configure network access for your needs.

Deploy ClickHouse on Deplomo for your analytical workload.

## Deploy ClickHouse

Deploy ClickHouse from a template and configure its storage and compute resources. Availability depends on your selected package and configuration.

[Get started with ClickHouse](https://panel.deplomo.com/signup)