How to Deploy ClickHouse on AWS

How do I deploy and run ClickHouse on AWS?

Deploying ClickHouse on AWS sets up a high-performance column-store database in the cloud for real-time analytics.

Welcome to the Galaxy, Guardian!

Oops! Something went wrong while submitting the form.

Description

Why run ClickHouse on AWS?

ClickHouse delivers sub-second analytics at petabyte scale. AWS offers elastic compute, SSD storage, and managed networking, making it simple to scale ClickHouse up or down without buying hardware.

What AWS services do I need?

Start with EC2 for compute, EBS gp3/io2 for storage, and optional S3 for backup.Use an Auto Scaling Group for replicas, an Application Load Balancer for read routing, and CloudWatch for metrics.

How do I size EC2 instances?

Select m7i or r7i families for balanced CPU and RAM. Allocate 8–16 vCPU and 32–64 GB RAM per node for mid-sized ecommerce workloads processing up to 2 TB of order data.

Which storage options work best?

Pick EBS gp3 (SSD) with 16K IOPS and 1 GB/s throughput for general use. Switch to io2 Block Express for write-heavy dashboards.Provision 3× data size to leave room for merges and backups.

How do I install ClickHouse on EC2?

Launch Amazon Linux 2023, enable swap, and run sudo yum install -y clickhouse-server clickhouse-client. Edit /etc/clickhouse-server/config.xml to set <listen_host>0.0.0.0</listen_host> and advertise internal DNS names.

How do I configure a cluster?

Create a ZooKeeper ensemble with AWS MSK or three t3.small EC2 nodes. In remote_servers.xml, declare shards and replicas referencing private IPs.Restart ClickHouse on each node.

How do I load ecommerce data?

Use clickhouse-client --query "INSERT INTO … FORMAT CSV" to batch-load S3-hosted exports. Parallelize uploads across instances with GNU Parallel or AWS DataSync.

Example: batch load Orders

aws s3 cp s3://shop-data/orders.csv - | clickhouse-client --query="INSERT INTO Orders FORMAT CSV"

How do I handle backups?

Schedule clickhouse-backup every hour. Store snapshots in S3 Glacier Deep Archive for low-cost retention. Replicate to another AWS Region for disaster recovery.

How do I monitor performance?

Export system.metrics to CloudWatch every minute.Alert on MergeTreeBackgroundExecutorPoolTask queue length > 100 and disk usage > 80 %.

Best practices for production

Use cgroups to reserve 75 % RAM for ClickHouse.
Place data volumes on separate EBS devices.
Encrypt EBS with KMS keys.
Enable TLS and mTLS for client traffic.

Why How to Deploy ClickHouse on AWS is important

How to Deploy ClickHouse on AWS Example Usage


-- Total revenue by day for the last 30 days
SELECT toDate(order_date)   AS day,
       sum(total_amount)    AS revenue
FROM   shop.Orders
WHERE  order_date >= today() - 30
GROUP  BY day
ORDER  BY day;

How to Deploy ClickHouse on AWS Syntax


-- Core ClickHouse DDL for an ecommerce schema
CREATE DATABASE IF NOT EXISTS shop;

CREATE TABLE shop.Customers (
    id UInt64,
    name String,
    email String,
    created_at DateTime
) ENGINE = MergeTree
ORDER BY id;

CREATE TABLE shop.Orders (
    id UInt64,
    customer_id UInt64,
    order_date DateTime,
    total_amount Decimal(12,2)
) ENGINE = ReplicatedMergeTree('/clickhouse/tables/{shard}/orders', '{replica}')
ORDER BY (customer_id, order_date);

CREATE TABLE shop.Products (
    id UInt64,
    name String,
    price Decimal(10,2),
    stock UInt32
) ENGINE = MergeTree
ORDER BY id;

CREATE TABLE shop.OrderItems (
    id UInt64,
    order_id UInt64,
    product_id UInt64,
    quantity UInt32
) ENGINE = MergeTree
ORDER BY (order_id, product_id);

-- Grant network access
sudo firewall-cmd --add-port=9000/tcp --permanent && sudo firewall-cmd --reload

Common Mistakes

Mistake: Using magnetic EBS volumes (sc1/st1). These drives cap at 250 MB/s, causing slow merges. Fix: Use gp3 or io2 SSD volumes with provisioned IOPS.
Mistake: Running one large instance. A single node lacks redundancy and limits parallelism. Fix: Start with three smaller replicas across different AZs.