# Integrate Amazon Aurora for MySQL with Databox Amazon Aurora is a cloud-native relational database engine from AWS that is fully compatible with MySQL while delivering up to five times the throughput of standard MySQL on the same hardware. Aurora clusters automatically replicate data across multiple Availability Zones, handle failover, and manage storage scaling without manual intervention. Connecting Amazon Aurora for MySQL to Databox lets you pull data directly from your Aurora cluster, build datasets using SQL queries, and visualize business-critical figures alongside data from your other connected tools. This article covers Aurora clusters running the **MySQL-compatible engine**. If your cluster uses the PostgreSQL-compatible engine, see [Integrate Amazon Aurora for PostgreSQL with Databox](/integrate-amazon-aurora-for-postgresql-with-databox) instead. The steps for configuring public access and security group rules in AWS are the same for both engine types. ## Connection If you've already established a connection, you can [reuse](/add-a-data-source) it to add new data sources to your Databox account. ### Step 1: Create a read-only MySQL user for Databox Databox only reads data from your database — it never writes to it. Create a dedicated MySQL user with `SELECT`-only privileges scoped to the Databox IP address. You can run these commands using a MySQL client connected to your Aurora cluster endpoint, or via the **Query Editor** in the AWS Management Console. **MySQL 8.0+ (modern syntax):** ```sql CREATE USER 'databox'@'52.4.198.118' IDENTIFIED BY 'your_secure_password'; GRANT SELECT ON your_database.* TO 'databox'@'52.4.198.118'; FLUSH PRIVILEGES; ``` **MySQL 5.7 (legacy single-statement syntax):** ```sql GRANT SELECT ON your_database.* TO 'databox'@'52.4.198.118' IDENTIFIED BY 'your_secure_password'; FLUSH PRIVILEGES; ``` Replace `your_database` with the name of the database you want to connect, and `your_secure_password` with a strong password. If you need to grant access to multiple databases, repeat the `GRANT` statement for each one. Avoid the following special characters in your password, as they can cause encoding issues when establishing the connection: ```, `'`, `"`, `/`, `\`, and spaces. ### Step 2: Enable public accessibility on your Aurora cluster By default, Aurora instances are not accessible from outside their VPC. To allow Databox to reach your cluster, each instance in the cluster must be configured as publicly accessible. 1. In the [AWS Management Console](https://console.aws.amazon.com/rds/), go to **Databases** and select your Aurora DB cluster. 2. Select an individual DB instance within the cluster (not the cluster itself). 3. Click **Modify**. 4. Under **Connectivity**, set **Public access** to **Yes**. 5. Click **Continue**, then choose **Apply immediately**. 6. Click **Modify DB instance** to save. 7. Repeat for any other instances in the cluster. For the cluster to be reachable after enabling public access, its subnet group must include subnets with an internet gateway attached. If connectivity still fails, verify that a route to `0.0.0.0/0` via an internet gateway exists in the associated route table. ### Step 3: Add the Databox IP to your VPC security group Aurora controls network access through VPC security groups. Add an inbound rule that permits TCP traffic on port `3306` from the Databox IP address. 1. In the [AWS Management Console](https://console.aws.amazon.com/rds/), go to **Databases** and select your Aurora DB cluster. 2. Under **Connectivity & security**, click the link to the **VPC security group** associated with the cluster. 3. Select the security group, then click **Edit inbound rules**. 4. Click **Add rule** and fill in: - **Type**: MySQL/Aurora - **Protocol**: TCP - **Port range**: 3306 - **Source**: Custom — enter `52.4.198.118/32` 5. Click **Save rules**. ### Step 4: Enter your Aurora connection details in Databox 1. In Databox, go to **Data Sources > + New connection**. 2. Search for **MySQL** and click **Connect**. 3. Fill in the connection form: - **Data source name** — a label for this connection in Databox. - **Host** — your Aurora cluster endpoint, found on the cluster's **Connectivity & security** tab in the AWS Console (e.g., `my-cluster.cluster-abc123.us-east-1.rds.amazonaws.com`). You can also use the **reader endpoint** (`my-cluster.cluster-ro-abc123.us-east-1.rds.amazonaws.com`) to route queries to read replicas only. - **Port** — the port your Aurora cluster listens on. The default for MySQL-compatible Aurora is `3306`. - **User** — the MySQL username created in [Step 1](#step-1-create-a-read-only-mysql-user-for-databox). - **Password** — the password for that user. - **Database name** (optional) — the specific database to connect to. Leave blank to connect at the server level. - **Timezone** — the time zone used to interpret date values in query results. Defaults to `Etc/UTC`. 4. Select an **SSL/TLS mode** (see [SSL/TLS](#ssltls) below). 5. Click **Connect**. connect ## SSL/TLS Databox offers three SSL/TLS modes when connecting to a database. Choose the one that matches your server's configuration. | Mode | Description | | --- | --- | | None | The connection is made without SSL/TLS encryption. Use this only when your server does not have SSL enabled. | | Use SSL/TLS with provider CA bundle | The connection uses SSL/TLS and authenticates the server using a regional CA bundle managed by your cloud provider (for example, Amazon RDS). When you check **Verify server certificate using regional CA bundle**, an additional **CA certificate bundle (ssl-ca)** field appears, where you can paste your provider's CA certificate. | | Use SSL/TLS with custom certificates | The connection uses SSL/TLS with certificates you supply directly. When **Verify server certificate** is checked, you must provide a **CA certificate (ssl-ca)**. You may also supply a **Client certificate (ssl-cert)** and **Client private key (ssl-key)** for mutual TLS. If **Verify server certificate** is unchecked, only the client certificate and private key fields are shown. | Amazon Aurora provides SSL/TLS certificates signed by AWS-managed certificate authorities. To use SSL with server certificate verification, download the appropriate CA certificate bundle from AWS and paste its contents into the **CA certificate bundle (ssl-ca)** field in Databox. For step-by-step instructions on configuring each SSL mode, see [Enable SSL/TLS for your database connection](/enable-ssl-tls-for-your-database-connection). ## Datasets The Amazon Aurora for MySQL integration supports the creation of [datasets](/understanding-datasets), which allow you to define and shape the specific data you want to use for reporting in Databox. Datasets make it easier to focus on the most relevant information, enabling you to filter, visualize, and analyze metrics across projects, teams, and clients without writing complex queries each time. ### Steps to create a dataset 1. **Select a table**: Pick the appropriate schema within that database. 2. **Select columns**: Browse and select the specific columns (fields) from your tables or views to include in your dataset. These columns define the structure and content of your dataset. ### Optional: Write SQL For more advanced use cases, you can write a **custom SQL query** instead of selecting columns manually. This allows you to: - Join multiple tables - Apply filters and aggregations - Format or transform data before importing it into Databox Your query must return a valid tabular result to be used as a dataset. ### Additional resources - [Amazon Aurora documentation](https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_AuroraOverview.html) — Official AWS docs for Amazon Aurora, covering cluster creation, connectivity, security, backups, global databases, and monitoring. - [Amazon Aurora MySQL-compatible edition](https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.AuroraMySQL.html) — MySQL-specific guidance within the Aurora User Guide, including supported versions, parameter groups, and engine-specific features. ## Resources For comprehensive details on metrics, data availability, templates, specifications, usage guidelines, and other key information, refer to the resources listed below. Yes. Databox accepts either the cluster endpoint or the reader endpoint. The reader endpoint (`my-cluster.cluster-ro-abc123.us-east-1.rds.amazonaws.com`) distributes read queries across Aurora Replicas and is a good choice for Databox since it only issues `SELECT` queries. Use the cluster endpoint if your cluster has no replicas. Aurora Serverless v2 uses standard MySQL connectivity and is supported — set it up the same way as a provisioned cluster. Aurora Serverless v1 uses the RDS Data API for connections and does not expose a standard TCP endpoint, so it is not compatible with the Databox connector. Check the following in order: 1. **Public access** is set to **Yes** on the DB instances within the cluster (under **Modify > Connectivity**). 2. The **VPC security group** has an inbound rule allowing TCP on port `3306` from `52.4.198.118/32`. 3. The subnet group includes subnets with a route to an internet gateway (`0.0.0.0/0`). 4. The MySQL user was created with `'databox'@'52.4.198.118'` as the host — not `'%'` or `'localhost'`. Run `FLUSH PRIVILEGES;` after any user or grant changes.   Ask Genie Get instant answers or help with your data using the in-app AI assistant. Talk to an expert For customers: Get help with your setup, strategy, or making the most of Databox. Book a demo New to Databox? See how it works and get guidance on getting started. Send an email Reach out to support for help with your account, data, or technical issues.