ClickHouse Analytics Database

This is a repackaged open source software product wherein additional charges apply for cloudimg support services.

Overview

ClickHouse is the open source column-oriented online analytical processing (OLAP) database built for sub-second queries over billions of rows. This AMI delivers ClickHouse fully installed and configured on a single node, so your analytics database is running within minutes of launch - no manual compilation, security hardening, or storage configuration required. Backed by 24/7 cloudimg technical support.

Why This AMI Over Self-Installation

Installing ClickHouse on a bare EC2 instance requires manual package setup, storage partitioning, credential management, and service hardening. This image eliminates that effort. Compared to self-deployment you get: pre-hardened authentication from first boot, a dedicated data volume already mounted, and expert support for cluster expansion and query tuning - all without managing the undifferentiated infrastructure work yourself.

AWS Integration

ClickHouse natively supports reading and writing data from Amazon S3, enabling cost-effective tiered storage and bulk data import/export. You can ingest streaming data from Amazon Kinesis or Amazon MSK (Managed Streaming for Apache Kafka) directly into ClickHouse tables. System metrics can be exported to Amazon CloudWatch for unified monitoring alongside your other AWS workloads.

Requirements and Sizing Guidance

Minimum recommended instance: 4 vCPUs and 16 GB RAM (e.g., r6i.xlarge or r5.xlarge). For heavier workloads exceeding 1 billion rows or concurrent query users, consider r6i.2xlarge or larger. The AMI uses a dedicated EBS volume for ClickHouse data - gp3 is recommended, sized to your dataset. Network ports to open in your security group: 8123 (HTTP interface and /play playground), 9000 (native TCP protocol), and 9009 (inter-server replication - restrict to private subnet if not clustering).

Authentication and Security

The image ships with the default user locked behind a password placeholder. On first boot, a one-shot service generates a strong, unique-per-instance password, writes it to a root-only file, and applies it via ALTER USER so the database never accepts unauthenticated connections. No shared or default credentials ship in the image. For encryption in transit, configure TLS on the HTTP and native interfaces using your own certificates. The dedicated EBS data volume supports AWS-managed encryption at rest when enabled at launch.

Data on Its Own Volume

ClickHouse data, metadata, and system tables live on a dedicated, independently resizable EBS volume mounted at theClickHouse data directory. This separation means you can grow storage, take snapshots, and manage backups independently of the OS disk - resize without downtime and snapshot your entire dataset in seconds via EBS.

What Is Included

ClickHouse server and the clickhouse-client command line tool installed from the officialClickHouse package repository, running the current stable line as a single node. The HTTP interface (including the built-in /play SQL playground), the native TCP protocol, and the inter-server replication port are all configured.ClickHouse is the only workload on the image, keeping resource consumption lean and predictable.

Quick Start

1. Launch the AMI on an r6i.xlarge or larger instance with a gp3 EBS data volume.

2. Open ports 8123 and 9000 in your security group.

3. SSH into the instance and read the generated password from the root-only file.

4. Connect via clickhouse-client or any HTTP client using the default user and generated password.

5. Open http://your-instance:8123/play in a browser for the built-in SQL playground.

6. Create databases and tables, then scale to a multi-node cluster using the user guide.

Use Cases

Real-time analytics dashboards and product telemetry. An e-commerce team ingesting hundreds of millions of clickstream events per day to power real-time conversion funnel dashboards. Log, event, and observability stores replacing costly managed solutions. Business intelligence and ad-hoc reporting over very large datasets. Time-series analysis for IoT and financial data.

cloudimg Support

24/7 technical support by email and live chat with a one-hour average response for critical issues. Our engineers help withClickHouse deployment, cluster expansion, schema design, query tuning, and database administration. Book a free30-minute architecture review to plan your deployment.

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