Supported data sources - Amazon QuickSight

Supported data sources

Amazon QuickSight supports a variety of data sources that you can use to provide data for analyses. The following data sources are supported.

Connecting to relational data

You can use any of the following relational data stores as data sources for Amazon QuickSight:

  • Amazon Athena

  • Amazon Aurora

  • Amazon OpenSearch Service

  • Amazon Redshift

  • Amazon Redshift Spectrum

  • Amazon S3

  • Amazon S3 Analytics

  • Apache Spark 2.0 or later

  • AWS IoT Analytics

  • Databricks (E2 Platform only) on Spark 1.6 or later, up to version 3.0

  • Exasol 7.1.2 or later

  • Google BigQuery

  • MariaDB 10.0 or later

  • Microsoft SQL Server 2012 or later

  • MySQL 5.7 or later


    Effective October 2023, the MySQL community has deprecated support for MySQL version 5.7. This means that Amazon QuickSight will no longer support new features, enhancements, bug fixes, or security patches for MySQL 5.7. Support for existing query workload will take place at a best effort basis. QuickSight customers can still use MySQL 5.7 datasets with QuickSight, but we encourage customers to upgrade their MySQL databases (DB) to major version 8.0 or higher. To see the statement provided by Amazon RDS, see Amazon RDS Extended Support opt-in behavior is changing. Upgrade your Amazon RDS for MySQL 5.7 database instances before February 29, 2024 to avoid potential increase in charges.

    Amazon RDS has updated their security settings for Amazon RDS MySQL 8.3. Any connections from QuickSight to Amazon RDS MySQL 8.3 are SSL-enabled by default. This is the only option available for MySQL 8.3. connections.

  • Oracle 12c or later

  • PostgreSQL 9.3.1 or later

  • Presto 0.167 or later

  • Snowflake

  • Starburst

  • Trino

  • Teradata 14.0 or later

  • Timestream


You can access additional data sources not listed here by linking or importing them through supported data sources.

Amazon Redshift clusters, Amazon Athena databases, and Amazon RDS instances must be in AWS. Other database instances must be in one of the following environments to be accessible from Amazon QuickSight:

  • Amazon EC2

  • Local (on-premises) databases

  • Data in a data center or some other internet-accessible environment

For more information, see Infrastructure security in Amazon QuickSight.

Importing file data

You can use files in Amazon S3 or on your local (on-premises) network as data sources. QuickSight supports files in the following formats:

  • CSV and TSV – Comma-delimited and tab-delimited text files

  • ELF and CLF – Extended and common log format files

  • JSON – Flat or semistructured data files

  • XLSX – Microsoft Excel files

QuickSight supports UTF-8 file encoding, but not UTF-8 (with BOM).

Files in Amazon S3 that have been compressed with zip, or gzip (, can be imported as-is. If you used another compression program for files in Amazon S3, or if the files are on your local network, remove compression before importing them.

JSON data

Amazon QuickSight natively supports JSON flat files and JSON semistructured data files.

You can either upload a JSON file or connect to your Amazon S3 bucket that contains JSON data. Amazon QuickSight automatically performs schema and type inference on JSON files and embedded JSON objects. Then it flattens the JSON, so you can analyze and visualize application-generated data.

Basic support for JSON flat-file data includes the following:

  • Inferring the schema

  • Determining data types

  • Flattening the data

  • Parsing JSON (JSON embedded objects) from flat files

Support for JSON file structures (.json) includes the following:

  • JSON records with structures

  • JSON records with root elements as arrays

You can also use the parseJson function to extract values from JSON objects in a text file. For example, if your CSV file has a JSON object embedded in one of the fields, you can extract a value from a specified key-value pair (KVP). For more information on how to do this, see parseJson.

The following JSON features aren't supported:

  • Reading JSON with a structure containing a list of records

  • List attributes and list objects within a JSON record; these are skipped during import

  • Customizing upload or configuration settings

  • parseJSON functions for SQL and analyses

  • Error messaging for invalid JSON

  • Extracting a JSON object from a JSON structure

  • Reading delimited JSON records

You can use the parseJson function to parse flat files during data preparation. This function extracts elements from valid JSON structures and lists.

The following JSON values are supported:

  • JSON object

  • String (double quoted)

  • Number (integer and float)

  • Boolean

  • NULL

Software as a service (SaaS) data

QuickSight can connect to a variety of Software as a Service (SaaS) data sources either by connecting directly or by using Open Authorization (OAuth).

SaaS sources that support direct connection include the following:

  • Jira

  • ServiceNow

SaaS sources that use OAuth require that you authorize the connection on the SaaS website. For this to work, QuickSight must be able to access the SaaS data source over the network. These sources include the following:

  • Adobe Analytics

  • GitHub

  • Salesforce

    You can use reports or objects in the following editions of Salesforce as data sources for Amazon QuickSight:

    • Enterprise Edition

    • Unlimited Edition

    • Developer Edition

To connect to on premises data sources, you need to add your data sources and a QuickSight-specific network interface to Amazon Virtual Private Cloud (Amazon VPC). When configured properly, a VPC based on Amazon VPC resembles a traditional network that you operate in your own data center. It enables you to secure and isolate traffic between resources. You define and control the network elements to suit your requirements, while still getting the benefit of cloud networking and the scalable infrastructure of AWS.

For detailed information, see Infrastructure security in Amazon QuickSight.