# T-SQL Published articles for T-SQL. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Is Azure SQL Database Hyperscale "distributed SQL"? DevFeed: [Is Azure SQL Database Hyperscale "distributed SQL"?]() Original publisher: [Read original article]() Author: Anna Hoffman Published: 2026-10-30T16:52:56Z Content type: article Language: en Sources: [Azure SQL Dev Corner]() Topics: [Azure SQL](), [sql-database](), [sql-server](), [Amazon Aurora](), [consistency](), [Transactions](), [read-replica](), [SQL]() Tags: [ai](), [ai-workloads](), [amazon-aurora](), [analytics](), [architecture](), [aws](), [azure](), [azure-sql](), [azure-sql-database](), [backup](), [backups](), [benchmark](), [capacity](), [cloud](), [commit](), [database](), [distributed](), [distributed-sql](), [hyperscale](), [sql](), [t-sql]() ### AI overview Azure SQL Database Hyperscale is a distributed architecture with a single-writer SQL engine. Compute replicas process queries, a log service handles durability and distributes log records, page servers hold data slices, and Azure Storage keeps the long-term copy and snapshots. This design supports automatic storage growth up to 128 TB, near-instant snapshot backups, restores largely independent of database size, and replicas that can be added without copying data. It retains SQL Server transaction semantics and T-SQL compatibility, but only one primary accepts writes; workloads requiring multiple writers face a different trade-off. In a Microsoft-commissioned comparison using HammerDB TPROC-C on a 2.3 TB database, Hyperscale Premium-series at 16 vCores delivered up to 52% higher performance and up to 51% better performance per dollar than Aurora PostgreSQL I/O-Optimized, leading at each tested concurrency level. The author cautions that benchmark results may not predict an individual workload and recommends testing it. ### Source excerpt In my last post, I broke down the Socrates paper, the research that became Azure SQL Database Hyperscale. Writing it made me want to tackle a question I think trips a lot of people up when they're choosing a database: is Azure SQL Database Hyperscale "distributed SQL"? It's a fair question. "Distributed SQL" has become [...] The post Is Azure SQL Database Hyperscale "distributed SQL"? appeared first on Azure SQL Dev Corner. ## Troubleshooting Data Mismatches with tablediff on Amazon RDS for SQL Server DevFeed: [Troubleshooting Data Mismatches with tablediff on Amazon RDS for SQL Server]() Original publisher: [Read original article]() Author: Kanchan Bhattacharyya Published: 2026-10-22T16:33:04Z Content type: article Language: en Sources: [AWS Database Blog]() Topics: [RDS for SQL Server](), [read-replica](), [sql-server](), [Amazon RDS](), [SQL](), [observability](), [Disaster Recovery](), [audit](), [Amazon S3]() Tags: [2022](), [2025](), [advanced-300](), [amazon-cloudwatch](), [amazon-ec2](), [amazon-elastic-compute-cloud-amazon-ec2](), [amazon-rds](), [amazon-simple-storage-service-amazon-s3](), [asynchronous](), [audit](), [best-practices](), [how-to](), [lag](), [rds-for-sql-server](), [read-replica](), [replication](), [scripts](), [sql-server](), [t-sql](), [technical-how-to](), [troubleshooting](), [utility]() ### AI overview After an Amazon RDS for SQL Server read replica catches up, tablediff can provide independent row-level parity evidence that replication metrics alone do not: compare the primary and replica only after `ReplicaLag`, `redo_queue_size`, and `log_send_queue_size` are all zero. Run it from a Windows EC2 client with access to both endpoints; target tables need a clustered primary key or unique index. It reports source-only, destination-only, and column-mismatched rows, and can generate T-SQL fixes. The replica is read-only, so remediation requires promotion, which is irreversible; regenerate the fix script after promotion and wrap its bare DML statements in an explicit transaction with a validation gate. Re-run tablediff to confirm zero differences. A fresh rebuild may be preferable for extensive or structural divergence. Comparisons scan whole tables and can give misleading results during active writes or redo, so run during a quiet period after queues drain. ### Source excerpt Learn how to use the SQL Server tablediff utility to validate an Amazon RDS for SQL Server read replica against its primary after a replication lag event, detect and classify row-level data mismatches, and apply auditable T-SQL fix scripts on a promoted replica instance. ## Canada's 2026 time zone updates: guidance for Microsoft SQL DevFeed: [Canada's 2026 time zone updates: guidance for Microsoft SQL]() Original publisher: [Read original article]() Author: Umachandar Jayachandran (UC) Published: 2026-10-15T05:21:10Z Content type: tutorial Language: en Sources: [Azure SQL Dev Corner]() Topics: [sql-server](), [timezone](), [Azure SQL]() Tags: [2026](), [azure-sql](), [azure-sql-database](), [azure-sql-managed-instance](), [canada](), [fabric-sql](), [fabric-sql-database](), [managed-instance](), [sql-server](), [t-sql](), [time]() ### AI overview Microsoft outlines interim time zone guidance for SQL Server on Windows and Linux, Azure SQL Database, and Azure SQL Managed Instance ahead of Canada's November 2026 changes. It explains regional offsets, temporary identifiers and workarounds, configuration scope, and migration considerations when final regional zones are unavailable. ### Source excerpt Affected locations in British Columbia, Alberta, and Manitoba will not turn their clocks back at 02:00 local time on November 1, 2026. They will remain at UTC−07:00, UTC−06:00, and UTC−05:00, respectively. Microsoft's interim guidance for British Columbia, Alberta, and Manitoba describes the new Windows time zones and temporary workarounds. SQL Server on Windows requires the [...] The post Canada's 2026 time zone updates: guidance for Microsoft SQL appeared first on Azure SQL Dev Corner. ## Migrate CLR code to AWS Lambda when upgrading Amazon RDS for SQL Server to 2025 DevFeed: [Migrate CLR code to AWS Lambda when upgrading Amazon RDS for SQL Server to 2025]() Original publisher: [Read original article]() Author: Raunak Gupta Published: 2026-10-12T16:11:15Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [AWS Lambda](), [RDS for SQL Server](), [sql-server](), [Amazon API Gateway](), [Serverless](), [CI/CD]() Tags: [advanced-300](), [amazon-api-gateway](), [aws-lambda](), [net](), [rds-for-sql-server](), [sql-server-2025](), [t-sql](), [technical-how-to]() ### AI overview This hands-on tutorial shows how to move SQL CLR logic that has no native T-SQL equivalent into an AWS Lambda function, then call it from Amazon RDS for SQL Server 2025 through API Gateway and sp_invoke_external_rest_endpoint. Its CSV example preserves quoted fields containing commas and line breaks. The article covers setup, credentials, access controls, performance, cost, and cleanup, and recommends the pattern for batch or file-level work because each call adds network latency. ### Source excerpt After upgrading Amazon RDS for SQL Server to 2017 or later, CLR strict security leaves user-defined CLR assemblies unusable. This post shows how to migrate CLR logic with no native T-SQL equivalent to an AWS Lambda function, invoked from SQL Server 2025 through sp_invoke_external_rest_endpoint behind Amazon API Gateway. ## PostgreSQL to SQL Field Notes: Connections DevFeed: [PostgreSQL to SQL Field Notes: Connections]() Original publisher: [Read original article]() Author: Jerry Nixon Published: 2026-10-06T16:39:17Z Content type: article Language: en Sources: [Azure SQL Dev Corner]() Topics: [Heroku Postgres](), [sql-server](), [PostgreSQL](), [connection pool](), [connection draining](), [locking]() Tags: [antipattern](), [architecture](), [azure-sql](), [c-sharp](), [concurrent](), [connect](), [connection-pool](), [connection-pooling](), [cost](), [database](), [microsoft-sql](), [modernize](), [net](), [postgresql](), [sql](), [sql-server-2025](), [t-sql]() ### AI overview The article compares PostgreSQL and Microsoft SQL connection models. PostgreSQL assigns a dedicated operating-system process to each connection, so developers commonly limit concurrent connections and manage pooling. Microsoft SQL uses workers on demand and typically relies on ADO.NET connection pooling, making idle connections less resource intensive. The article recommends letting the database and client pool manage most connection scenarios. ### Source excerpt Welcome to SQL First, welcome to SQL! You're going to like this. Upgrading from PostgreSQL is real work, and depending on your old database, this process will vary widely in complexity. I am confident that you're going to love the mindful and modern features of SQL. Take your time, make the most of the resources [...] The post PostgreSQL to SQL Field Notes: Connections appeared first on Azure SQL Dev Corner. ## DiskANN Vector Index and Vector Search Are Now Generally Available in Azure SQL DevFeed: [DiskANN Vector Index and Vector Search Are Now Generally Available in Azure SQL]() Original publisher: [Read original article]() Author: Pooja Kamath Published: 2026-09-29T15:00:22Z Content type: release Language: en Sources: [Azure SQL Dev Corner]() Topics: [Azure SQL](), [sql-database](), [cosine similarity search](), [ann](), [vectorization techniques](), [SQL]() Tags: [ai](), [approximate-nearest-neighbor-search](), [azure-sql](), [azure-sql-database](), [diskann](), [embeddings](), [fabric-sql-database](), [hyperscale](), [similarity](), [sql](), [t-sql](), [vector-index](), [vector-search](), [vectors]() ### AI overview DiskANN vector indexing and search are now generally available in Azure SQL Database, Azure SQL Managed Instance with the always-up-to-date update policy, and SQL database in Microsoft Fabric. The index uses approximate nearest-neighbor search to find similar vectors efficiently as datasets grow, and can use SSD-backed storage to limit reliance on RAM. Applications can combine vector similarity search with relational data, filters, joins, security policies, and transactions. ### Source excerpt Today, we are announcing the general availability of DiskANN Vector Index & Search across Azure SQL Database, Azure SQL Managed Instance with the always-up-to-date update policy, and SQL database in Microsoft Fabric. DiskANN brings scalable approximate nearest-neighbor search directly to the SQL engine. Developers can store vectors alongside relational data and combine vector similarity with [...] The post DiskANN Vector Index and Vector Search Are Now Generally Available in Azure SQL appeared first on Azure SQL Dev Corner. ## What's new across Microsoft SQL at SQLCon/FabCon Europe 2026 DevFeed: [What's new across Microsoft SQL at SQLCon/FabCon Europe 2026]() Original publisher: [Read original article]() Author: Anna Hoffman Published: 2026-09-29T07:30:04Z Content type: news Language: en Sources: [Azure SQL Dev Corner]() Topics: [sql-server](), [Azure SQL](), [Azure]() Tags: [2026](), [ai](), [azure](), [azure-sql](), [data-api-builder](), [drivers](), [fabric-sql-database](), [hyperscale](), [microsoft](), [microsoft-sql](), [sql-database-in-fabric](), [sql-database-projects](), [sql-mcp-server](), [sql-server-2025](), [t-sql](), [vector-search](), [vectors](), [visual-studio-code](), [vs-code]() ### AI overview Microsoft highlights SQL Server and Azure SQL updates announced at SQLCon and FabCon Europe 2026, including disconnected Azure Local availability, expanded Azure Arc regions, sovereign cloud support, VM provisioning changes, Linux updates, and preview migration tools. ### Source excerpt Live From Barcelona Woo! I'm posting this live from the first ever European SQLCon (joint conference with FabCon EU), and the second ever SQLCon. The energy here is great, as the community comes together in Barcelona and as we prepare to go on the keynote stage and share what's new! A heartfelt nod to the [...] The post What's new across Microsoft SQL at SQLCon/FabCon Europe 2026 appeared first on Azure SQL Dev Corner. ## Announcing the Public Preview of Local Time Zone Support in Azure SQL Database DevFeed: [Announcing the Public Preview of Local Time Zone Support in Azure SQL Database]() Original publisher: [Read original article]() Author: Umachandar Jayachandran (UC) Published: 2026-09-28T15:00:17Z Content type: release Language: en Sources: [Azure SQL Dev Corner]() Topics: [Azure SQL](), [SQL](), [timezone](), [sql-server](), [MySQL](), [Oracle Database]() Tags: [azure-sql](), [azure-sql-database](), [database](), [sql](), [t-sql](), [time]() ### AI overview Azure SQL Database now offers a public preview of configurable time zones at the database or session level using T-SQL. The database setting persists across connections and can be changed after creation; a session setting overrides it for one connection. Secondary replica databases inherit the primary replica's setting. ### Source excerpt We are thrilled to announce the public preview of local time zone support in Azure SQL Database. Starting today, you can configure the time zone directly at the database or session level -- all from T-SQL, without changing any infrastructure settings. This feature addresses one of the most consistently requested capabilities from the Azure SQL [...] The post Announcing the Public Preview of Local Time Zone Support in Azure SQL Database appeared first on Azure SQL Dev Corner. ## PostgreSQL to SQL Field Notes: Date & Time DevFeed: [PostgreSQL to SQL Field Notes: Date & Time]() Original publisher: [Read original article]() Author: Jerry Nixon Published: 2026-09-21T22:44:58Z Content type: tutorial Language: en Sources: [Azure SQL Dev Corner]() Topics: [PostgreSQL](), [sql-server](), [DateTime](), [SQL]() Tags: [azure-sql](), [dev](), [developer](), [microsoft-sql](), [modernize](), [postgresql](), [precision](), [sql-server](), [sql-server-2025](), [t-sql](), [time]() ### AI overview This tutorial explains date and time differences developers should understand when moving from PostgreSQL to SQL Server, including timestamp types, time-zone handling, offsets, fractional-second precision, and storage behavior. ### Source excerpt Moving from PostgreSQL to SQL Server? Learn the key differences between timestamp, timestamptz, datetime2, and datetimeoffset, including precision, time zones, offsets, and storage. The post PostgreSQL to SQL Field Notes: Date & Time appeared first on Azure SQL Dev Corner. ## SQL Decomposition in a Nutshell DevFeed: [SQL Decomposition in a Nutshell]() Original publisher: [Read original article]() Author: Jerry Nixon Published: 2026-09-03T20:06:28Z Content type: article Language: en Sources: [Azure SQL Dev Corner]() Topics: [SQL](), [Software Engineering](), [Database](), [software-architecture](), [hybrid-search]() Tags: [azure-sql](), [database](), [development](), [hybrid-search](), [maintainability](), [software-design](), [sql](), [t-sql]() ### AI overview This article explains how software design principles such as decomposition, encapsulation, statelessness, and clear contracts apply to complex T-SQL and database logic. It uses hybrid search as an example of separating responsibilities into components that are easier to test, diagnose, reuse, and maintain. ### Source excerpt Good software design principles apply inside the database too. See how decomposition, encapsulation, statelessness, and clear contracts can make complex T-SQL easier to read, test, reuse, and maintain. The post SQL Decomposition in a Nutshell appeared first on Azure SQL Dev Corner. ## Safely Evolving Production SQL Schemas Without Downtime DevFeed: [Safely Evolving Production SQL Schemas Without Downtime]() Original publisher: [Read original article]() Author: Jerry Nixon Published: 2026-09-03T19:09:04Z Content type: tutorial Language: en Sources: [Azure SQL Dev Corner]() Topics: [Structured-data](), [migration](), [Database](), [SQL](), [integrity](), [Deployment]() Tags: [azure-sql](), [database](), [database-change-management](), [deploy](), [downtime](), [migration](), [production](), [safely](), [schema](), [strategy](), [t-sql]() ### AI overview A phased approach to changing a production SQL schema while applications remain online. The article describes expanding the schema, supporting old and new application versions, and sequencing database and application deployments. ### Source excerpt Schema changes are inevitable, but downtime doesn't have to be. Learn a phased approach to safely evolve a production SQL schema while applications remain online. The post Advocating for Uptime: The 6 Phases of Change appeared first on Azure SQL Dev Corner. ## SQL Server login failures: how to monitor, report, and alert on them (complete guide) DevFeed: [SQL Server login failures: how to monitor, report, and alert on them (complete guide)]() Original publisher: [Read original article]() Author: Edward Pollack Published: 2026-09-02T12:00:00Z Content type: tutorial Language: en Sources: [Simple Talk]() Topics: [sql-server](), [Monitoring](), [Security](), [Database](), [Logging]() Tags: [alert](), [database](), [database-administration](), [databases](), [featured](), [how-to](), [logging](), [monitoring](), [security](), [sql](), [sql-server](), [t-sql](), [t-sql-programming]() ### AI overview A practical guide to detecting SQL Server login failures, filtering and aggregating error-log data with T-SQL and xp_readerrorlog, and automatically emailing summary alerts. It explains how failures can indicate configuration problems, application bugs, password issues, or unauthorized access attempts. ### Source excerpt Learn how to detect and report SQL Server login failures using T-SQL and xp_readerrorlog. Includes ready-to-use scripts for filtering, aggregating, and emailing alerts.... The post SQL Server login failures: how to monitor, report, and alert on them (complete guide) appeared first on Simple Talk. ## Beyond Vector Indexes: Azure SQL Brings Optimizer Intelligence to Vector Search DevFeed: [Beyond Vector Indexes: Azure SQL Brings Optimizer Intelligence to Vector Search]() Original publisher: [Read original article]() Author: Pooja Kamath Published: 2026-08-17T11:22:09Z Content type: article Language: en Sources: [Azure SQL Dev Corner]() Topics: [Azure SQL](), [AI search](), [SQL](), [Database](), [software-development]() Tags: [ai](), [application](), [applications](), [azure-openai](), [azure-sql](), [azure-sql-database](), [benchmarks](), [customer](), [data](), [database](), [developers](), [diskann](), [hyperscale](), [indexes](), [metrics](), [openai](), [performance](), [production-ai](), [queries](), [retrieval](), [scale](), [search](), [sql](), [t-sql](), [vector](), [vector-index](), [vector-search](), [vectors]() ### AI overview This article explains why production AI retrieval involves more than vector-index performance. It describes how Azure SQL can optimize vector search together with SQL filters, joins, security policies, ranking logic, and operational data. ### Source excerpt Why production AI retrieval depends on more than vector index performance. It's easy to think of AI retrieval as a vector search problem. For many developers, the first conversation starts with vector index benchmarks: How many queries per second can it handle? What's the latency? What's the recall? How well does it scale? Those metrics [...] The post Beyond Vector Indexes: Azure SQL Brings Optimizer Intelligence to Vector Search appeared first on Azure SQL Dev Corner. ## How to Pass a Table Valued Parameter to a T-SQL Function with jOOQ DevFeed: [How to Pass a Table Valued Parameter to a T-SQL Function with jOOQ]() Original publisher: [Read original article]() Author: lukaseder Published: 2023-04-25T12:16:30Z Content type: tutorial Language: en Sources: [jOOQ]() Topics: [sql-server](), [SQL](), [Java](), [Code]() Tags: [code](), [code-generation](), [code-generator](), [how-to](), [java](), [jdbc](), [jooq](), [jooq-in-use](), [sql-server](), [t-sql](), [table-valued-function](), [table-valued-parameter]() ### AI overview This tutorial explains how to pass a Microsoft T-SQL table-valued parameter to a function using jOOQ. It covers native T-SQL and JDBC usage, then shows how jOOQ's code generator produces Java types and methods for calling the function and accessing its result rows. ### Source excerpt Microsoft T-SQL supports a language feature called table-valued parameter (TVP), which is a parameter of a table type that can be passed to a stored procedure or function. For example, you may write: This function takes a table-valued parameter (TVP), and produces a result set containing the cross product of the parameter table with itself. ... Continue reading How to Pass a Table Valued Parameter to a T-SQL Function with jOOQ -> ## The Best Way to Call Stored Procedures from Java: With jOOQ DevFeed: [The Best Way to Call Stored Procedures from Java: With jOOQ]() Original publisher: [Read original article]() Author: lukaseder Published: 2022-07-28T13:11:59Z Content type: tutorial Language: en Sources: [jOOQ]() Topics: [Code generation](), [Java](), [SQL](), [data-processing](), [Server]() Tags: [code-generation](), [code-generator](), [data-processing](), [java](), [jdbc](), [jdbc-drivers](), [jooq](), [jooq-in-use](), [oracle](), [pl-pgsql](), [pl-sql](), [postgresql](), [rdbms](), [schema](), [sql](), [stored-functions](), [stored-procedures](), [t-sql](), [udts]() ### AI overview This tutorial explains how to call stored procedures from Java using jOOQ-generated code. It contrasts JDBC calls with generated procedure stubs and convenience methods, covering parameter handling, database types, and support for procedures, functions, packages, and UDTs. ### Source excerpt jOOQ is mainly known for its powerful type safe, embedded, dynamic SQL capabilities that are made available through code generation. However, a secondary use case of code generation is to use it for stored procedures (possibly exclusively for stored procedures). Stored procedures are powerful ways of moving complex data processing logic to the server. This ... Continue reading The Best Way to Call Stored Procedures from Java: With jOOQ ->