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articles/synapse-analytics/sql/overview-features.md

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@@ -47,7 +47,7 @@ Consumption models in Synapse SQL enable you to use different database objects.
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Query languages used in Synapse SQL can have different supported features depending on consumption model. The following table outlines the most important query language differences in Transact-SQL dialects:
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| Query language | Dedicated | Serverless |
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| Statement | Dedicated | Serverless |
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| --- | --- | --- |
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| **SELECT statement** | Yes. `SELECT` statement is supported, but some Transact-SQL query clauses, such as [FOR XML/FOR JSON](/sql/t-sql/queries/select-for-clause-transact-sql?view=azure-sqldw-latest&preserve-view=true), [MATCH](/sql/t-sql/queries/match-sql-graph?view=azure-sqldw-latest&preserve-view=true), OFFSET/FETCH are not supported. | Yes, `SELECT` statement is supported, but some Transact-SQL query clauses like [FOR XML](/sql/t-sql/queries/select-for-clause-transact-sql?view=azure-sqldw-latest&preserve-view=true), [MATCH](/sql/t-sql/queries/match-sql-graph?view=azure-sqldw-latest&preserve-view=true), [PREDICT](/sql/t-sql/queries/predict-transact-sql?view=azure-sqldw-latest&preserve-view=true), GROUPNG SETS, and the query hints are not supported. |
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| **INSERT statement** | Yes | No. Upload new data to Data Lake using Spark or other tools. Use Azure Cosmos DB with the analytical storage for highly transactional workloads. You can use [CETAS](/sql/t-sql/statements/create-external-table-as-select-transact-sql?view=azure-sqldw-latest&preserve-view=true) to create an external table and insert data. |
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Synapse SQL pools enable you to use built-in security features to secure your data and control access. The following table compares high-level differences between Synapse SQL consumption models.
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| Security | Dedicated | Serverless |
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| Feature | Dedicated | Serverless |
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| --- | --- | --- |
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| **Logins** | N/A (only contained users are supported in databases) | Yes, server-level Azure AD and SQL logins are supported. |
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| **Users** | N/A (only contained users are supported in databases) | Yes, database users are supported. |
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Data that is analyzed can be stored on various storage types. The following table lists all available storage options:
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| Storage type | Dedicated | Serverless |
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| Storage type | Dedicated | Serverless |
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| --- | --- | --- |
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| **Internal storage** | Yes | No, data is placed in Azure Data Lake or [Azure Cosmos DB analytical storage](query-cosmos-db-analytical-store.md). |
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| **Azure Data Lake v2** | Yes | Yes, you can use external tables and the `OPENROWSET` function to read data from ADLS. Learn here how to [setup access control](develop-storage-files-storage-access-control.md). |
@@ -156,7 +156,7 @@ Data that is analyzed can be stored on various storage types. The following tabl
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Data that is analyzed can be stored in various storage formats. The following table lists all available data formats that can be analyzed:
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| Data formats | Dedicated | Serverless |
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| Data format | Dedicated | Serverless |
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| --- | --- | --- |
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| **Delimited** | [Yes](/sql/t-sql/statements/create-external-file-format-transact-sql?view=azure-sqldw-latest&preserve-view=true) | Yes, you can [query delimited files](query-single-csv-file.md). |
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| **CSV** | Yes (multi-character delimiters not supported) | Yes, you can [query CSV files](query-single-csv-file.md). For better performance use PARSER_VERSION 2.0 that provides [faster parsing](develop-openrowset.md#fast-delimited-text-parsing). If you are appending rows to your CSV files, make sure that you [query the files as appendable](query-single-csv-file.md#querying-appendable-files). |

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