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Open this panel on your other device and enter the same code.
Starts this lesson and continues through 25 more to the end of the course.
There are two authoritative lists of what Amazon Quick Sight connects to, and they don't line up.
The user guide list (Supported data sources,
verified 2026-08-16) is organized by how a human thinks: relational stores, files, SaaS, local data.
The API list is the Type enum on
CreateDataSource —
38 values, organized by nothing at all, and containing things the user guide page doesn't mention
(GOOGLESHEETS, WEB_CRAWLER, QBUSINESS, S3_KNOWLEDGE_BASE).
You need both. The user guide tells you whether a connection is possible; the enum tells you what to type. When you automate — and Q7 assumes you will — the enum is the one that counts.
From the user guide, verbatim list (verified 2026-08-16): Amazon Athena, Amazon Aurora, AWS Glue Data Catalog ("accessed using AWS Glue data catalog compatible services, such as Athena or Redshift Spectrum"), Amazon OpenSearch Service, Amazon Redshift, Amazon Redshift Spectrum, Amazon S3, Amazon S3 Analytics, Amazon S3 Tables, Apache Impala, Apache Spark 2.0+, AWS IoT Analytics, Databricks (E2 platform only, Spark 1.6–3.0), Exasol 7.1.2+, Google BigQuery, MariaDB 10.0+, Microsoft SQL Server 2012+, MySQL 5.7+, Oracle 12c+, PostgreSQL 9.3.1+, Presto 0.167+, Snowflake, Starburst, Trino, Teradata 14.0+, Timestream.
Notice what's not a data source: Glue is not directly connectable. You reach Glue Data Catalog tables through Athena or Redshift Spectrum. Teams migrating from other BI tools ask for a "Glue connector" constantly; the answer is "point Athena at it."
Three version notes from the same page that turn into tickets:
This paragraph of the user guide does more work than any other (verbatim, verified 2026-08-16):
"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 Quick Sight: Amazon EC2, Local (on-premises) databases, Data in a data center or some other internet-accessible environment."
So a self-managed PostgreSQL box in your basement is a legitimate data source — if there's a network path (lesson 4). But you cannot point Quick Sight at, say, a Redshift-wire-compatible service running outside AWS and call it Redshift.
Supported formats: CSV/TSV, ELF/CLF (extended/common log), JSON, XLSX. Encoding is UTF-8 — and explicitly not UTF-8 with BOM. Files in S3 compressed with zip or gzip import as-is; any other compression, or compressed files uploaded from your local network, must be decompressed first.
The JSON support has documented edges (all verbatim from the supported-data-sources page): schema
and type inference, flattening, and embedded-object parsing are supported; not supported are
"a structure containing a list of records", list attributes ("skipped during import"), custom upload
settings, and — the quiet one — "error messaging for invalid JSON". A malformed JSON file
doesn't necessarily announce itself. Remember RowsDropped from Q2 lesson 3? This is one of the
things that feeds it.
Per-file shape limits, from Data source quotas (verified 2026-08-16):
| Limit | Value |
|---|---|
| Columns per file (or per query result set) | 2,000 |
| Characters per column name | 127 |
| Characters per field | 2,047 (65,534 in the "new data preparation experience") |
| Files per S3 manifest | 1,000 |
⚠️ The 2,000-column limit doesn't block the import — "File imports and query result sets can contain more than 2,000 columns", but you must then manually exclude fields in dataset settings until fewer than 2,000 remain (per the Service Quotas description of "Data Prep: Fields per dataset", which is not adjustable). Wide event tables hit this.
Direct connection: Jira, ServiceNow. Via OAuth (authorize on the SaaS site): Adobe Analytics, GitHub, Salesforce. For Salesforce, only Enterprise, Unlimited, and Developer editions are supported as sources.
Hold onto the Jira/ServiceNow pair — lesson 2 shows they're also the two sources that can't use Secrets Manager credentials.
The full Type valid values, verbatim from CreateDataSource (verified 2026-08-16):
ADOBE_ANALYTICS | AMAZON_ELASTICSEARCH | ATHENA | AURORA | AURORA_POSTGRESQL |
AWS_IOT_ANALYTICS | GITHUB | JIRA | MARIADB | MYSQL | ORACLE | POSTGRESQL |
PRESTO | REDSHIFT | S3 | S3_TABLES | SALESFORCE | SERVICENOW | SNOWFLAKE |
SPARK | SQLSERVER | TERADATA | TWITTER | TIMESTREAM | AMAZON_OPENSEARCH |
EXASOL | DATABRICKS | STARBURST | TRINO | BIGQUERY | GOOGLESHEETS |
GOOGLE_DRIVE | CONFLUENCE | SHAREPOINT | ONE_DRIVE | WEB_CRAWLER |
S3_KNOWLEDGE_BASE | QBUSINESS
Thirty-eight values, and they are a geological record:
TWITTER is still in the enum years after the product it points at renamed itself. AWS enums are
append-only in practice — this is the same reason quicksight survived the Quick Suite rename.AMAZON_ELASTICSEARCH and AMAZON_OPENSEARCH. The API page says,
in the Type documentation itself: "Use AMAZON_ELASTICSEARCH for Amazon OpenSearch Service."
Both values are valid; the old one is the documented recommendation. Expect either in any
account you inherit, and don't "fix" one to the other without testing — they are distinct types
with distinct parameter objects (AmazonElasticsearchParameters vs AmazonOpenSearchParameters).AURORA and AURORA_POSTGRESQL are separate types. Aurora MySQL goes under AURORA. Pick wrong
and the parameter validation fails before a packet ever leaves the building..csv.gz file importable as-is, and what breaks if the same
file is bzip2-compressed?Type does AWS document you should
use, and what's the trap?AMAZON_ELASTICSEARCH — the CreateDataSource page says to use it for OpenSearch Service. The
trap is that AMAZON_OPENSEARCH also exists and is also valid, so two data sources pointing at
the same domain can carry different types.aws quicksight list-data-sources against a real account; match each returned Type
to the enum and find at least one surprise (there's usually a fossil).