# SQL Server Published articles for SQL Server. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Agoda Replaces 72-Shard SQL Server Price Cache with DragonflyDB DevFeed: [Agoda Replaces 72-Shard SQL Server Price Cache with DragonflyDB]() Original publisher: [Read original article]() Author: Leela Kumili Published: 2026-09-14T13:48:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [Cache](), [Caching](), [migration](), [sql-server](), [Latency](), [Prometheus]() Tags: [a-b-testing](), [agoda-price-cache-dragonflydb](), [architecture-design](), [cache](), [caching](), [development](), [devops](), [distributed-cache](), [distributed-data](), [distributed-systems](), [latency](), [microservices](), [migration](), [news](), [prometheus](), [redis](), [sql-server]() ### AI overview Agoda migrated its 1.5 TB hotel Price Cache from 72 Microsoft SQL Server shards to DragonflyDB. The staged migration used workload testing, dual reads, parity metrics, and gradual traffic shifting; Agoda reported substantially lower P99 read latency. ### Source excerpt Agoda migrated its 1.5 TB hotel Price Cache from 72 SQL Server shards to DragonflyDB to handle growing read and write volumes. The migration used staged dual reads, parity validation, gradual traffic shifting, and decentralized failover detection. Agoda reports an approximately eightfold reduction in P99 read latency, with two DragonflyDB clusters providing high availability. By Leela Kumili ## Kaspersky report examines BitLocker ransomware attacks in Mexico and Colombia DevFeed: [Kaspersky report examines BitLocker ransomware attacks in Mexico and Colombia]() Original publisher: [Read original article]() Author: Kaspersky\_Lab ("Лаборатория Касперского") Published: 2026-07-27T19:52:29Z Content type: news Language: ru Sources: ["Лаборатория Касперского" RU]() Topics: [Security](), [Windows](), [sql-server]() Tags: [bitlocker](), [github](), [mesh](), [ransomware](), [rdp](), [security](), [sql-server](), [tag-9fe8963de219](), [windows]() ### AI overview A Kaspersky report examines ransomware incidents in Mexico and Colombia in which attackers used Windows BitLocker to encrypt organizational data. The reported entry points included exposed RDP and a misconfigured Microsoft SQL Server containing credentials published in GitHub code. ### Source excerpt Свежий отчет "Лаборатории Касперского" разбирает два недавних инцидента в Латинской Америке, в ходе которых организации стали жертвой кибервымогателей. Оба инцидента, произошедшие в мае этого года в Мексике и в июне в Колумбии, удалось подробно проанализировать, в результате чего стали понятны методы взлома корпоративной инфраструктуры, а также дальнейшие шаги киберпреступников. Примечательно, что в обоих случаях для шифрования данных с последующим требованием выкупа использовался штатный инструмент Windows, известный как BitLocker. Значок, указывающий на то, что диск зашифрован, стал первым признаком кибератаки, который заметили в организации. Точкой входа в инциденте, произошедшем в Колумбии, стала доступная из Интернета служба удаленного рабочего стола (RDP) на сервере, к которому, в свою очередь, был подключен жесткий диск объемом 8 терабайт с критически важными финансовыми данными. Злоумышленники сначала получили контроль над системой, изменили учетные данные пользователей, а затем применили шифрование. Еще одной любопытной особенностью данной атаки стала печать записки с требованием выкупа прямо на корпоративных принтерах в офисе организации. Читать далее ## How to Migrate from SQL Server to PostgreSQL HA for Dockerized Apps DevFeed: [How to Migrate from SQL Server to PostgreSQL HA for Dockerized Apps]() Original publisher: [Read original article]() Author: Jessie Baynas Published: 2026-05-28T07:18:00Z Content type: tutorial Language: en Sources: [SeveralNines]() Topics: [PostgreSQL](), [sql-server](), [migration](), [Database Migration](), [Replication](), [Docker Compose](), [Architecture & Design](), [DevOps](), [Monitoring]() Tags: [cloud-native](), [database-general](), [database-migration](), [deployment](), [devops](), [failover](), [migration](), [monitoring](), [open-source](), [postgresql](), [replication](), [sql-server](), [validation]() ### AI overview This tutorial explains how to migrate a database from Microsoft SQL Server to PostgreSQL for Dockerized applications. It separates schema migration with pgloader from bulk data export using BCP and import with PostgreSQL COPY, and describes a setup involving streaming replication and ClusterControl for deployment, monitoring, and failover. ### Source excerpt For many organizations, migrating from Microsoft SQL Server to PostgreSQL is no longer only about reducing licensing costs. The transition is often part of a broader modernization initiative focused on improving flexibility, scalability, and operational efficiency. PostgreSQL has evolved into one of the most mature open-source database platforms available today. It is widely adopted across [...] The post How to Migrate from SQL Server to PostgreSQL HA for Dockerized Apps appeared first on Severalnines. ## Introducing Apache Arrow Support in mssql-python DevFeed: [Introducing Apache Arrow Support in mssql-python]() Original publisher: [Read original article]() Author: Saumya Garg Published: 2026-05-04T04:33:00Z Content type: release Language: en Sources: [Microsoft Python Engineering]() Topics: [sql-server](), [data-processing](), [interoperability](), [data](), [pandas]() Tags: [apache-arrow](), [arrow](), [azure](), [azure-sql](), [client-driver](), [data-processing](), [interoperability](), [pandas](), [python](), [python-driver-for-azure-sql](), [python-driver-for-sql-server](), [sql-server](), [sql-server-2025](), [zero-copy]() ### AI overview Microsoft introduces Apache Arrow support in mssql-python, enabling SQL Server data to be fetched directly into Arrow structures for Polars, Pandas, DuckDB, and other Arrow-native libraries. The approach is intended to reduce Python object creation and memory overhead during data processing. ### Source excerpt Reviewed by Sumit Sarabhai Fetching a million rows from SQL Server into a Polars DataFrame used to mean a million Python objects, a million GC allocations, and then throwing it all away to build a DataFrame. Not anymore. mssql-python now supports fetching SQL Server data directly as Apache Arrow structures - a faster and more [...] The post Introducing Apache Arrow Support in mssql-python appeared first on Microsoft for Python Developers Blog. ## Walking Through an Unplanned Failover: SQL Server Availability Groups on Kubernetes DevFeed: [Walking Through an Unplanned Failover: SQL Server Availability Groups on Kubernetes]() Original publisher: [Read original article]() Author: Anthony Nocentino Published: 2026-04-19T15:00:00Z Content type: tutorial Language: en Sources: [Kubernetes on Anthony Nocentino's Blog]() Topics: [sql-server](), [Availability](), [Kubernetes](), [Databases]() Tags: [automatic](), [availability-groups](), [container](), [containers](), [crash](), [database](), [failover](), [kubernetes](), [load](), [open-source](), [operator](), [recovery](), [sql-server](), [test]() ### AI overview This walkthrough tests unplanned SQL Server Availability Group failover on Kubernetes by force-deleting the current primary pod under idle and sustained HammerDB TPC-C load. Across six force-deletes, the operator automatically promoted new primaries and restored all three replicas, with the article examining detection, recovery behavior, logs, and timing. ### Source excerpt In my planned failover walkthrough, I showed what happens when you deliberately move the primary role to another replica. That's the easy case. Now I want to show what happens when the primary pod just disappears unexpectedly, like during a node failure or a container crash. No graceful shutdown, no demotion, just gone. I ran two test scenarios, each cycling the primary role across all three pods by force-deleting the current primary three times in a row. First, a 5GB TPC-C database idle. Then, that same 5GB database under sustained HammerDB TPC-C load. Six force-deletes total, six successful automatic failovers. I'll walk through the error log from the promoted replica, the operator's detection and recovery behavior, and the full timing data. ## Walking Through a Planned Failover: SQL Server Always On Availability Groups on Kubernetes DevFeed: [Walking Through a Planned Failover: SQL Server Always On Availability Groups on Kubernetes]() Original publisher: [Read original article]() Author: Anthony Nocentino Published: 2026-04-19T05:00:00Z Content type: tutorial Language: en Sources: [Kubernetes on Anthony Nocentino's Blog]() Topics: [sql-server](), [Kubernetes](), [Availability]() Tags: [availability-groups](), [containers](), [failover](), [kubernetes](), [open-source](), [operator](), [sql-server]() ### AI overview A walkthrough of planned failover rotation for a three-replica SQL Server Availability Group managed by sql-on-k8s-operator on Kubernetes. It examines SQL Server error logs, operator reconciliation behavior, and timing under both an idle database and a sustained TPC-C workload. ### Source excerpt When building the sql-on-k8s-operator, I wanted to make sure it could handle both planned and unplanned failovers. The easy case is a planned failover, where you deliberately move the primary role to another replica. The harder case is an unplanned failover, where the primary pod just disappears. The operator needs to handle both. I recently ran a full planned failover rotation on a three-replica SQL Server Availability Group managed by sql-on-k8s-operator, and I want to show you exactly what happens inside SQL Server and the operator during each hop. If you've been following my Introducing the SQL Server on Kubernetes Operator post, this is the logical next step: what does the error log actually look like during a planned failover, what does the operator do in response, and how long does the whole thing take? ## Introducing the SQL Server on Kubernetes Operator DevFeed: [Introducing the SQL Server on Kubernetes Operator]() Original publisher: [Read original article]() Author: Anthony Nocentino Published: 2026-04-12T05:00:00Z Content type: tutorial Language: en Sources: [Kubernetes on Anthony Nocentino's Blog]() Topics: [Kubernetes](), [sql-server](), [Availability](), [Disaster Recovery](), [Open Source]() Tags: [automated](), [automatic](), [availability](), [availability-groups](), [containers](), [disaster-recovery](), [failover](), [high-availability](), [kubernetes](), [open-source](), [operator](), [sql-server]() ### AI overview This tutorial introduces sql-on-k8s-operator, an open-source Kubernetes operator for managing SQL Server workloads. It addresses high availability and disaster recovery by automating lifecycle management, failover, and Always On Availability Group setup, and demonstrates deployment with custom resources. ### Source excerpt Are you considering replatforming your SQL Server workload due to recent vendor changes, but still need high availability and disaster recovery? You're not alone. One of the challenges with running SQL Server on Kubernetes is that there's no Kubernetes operator available. That means no automated lifecycle management, no automatic failover, and no standard way to bootstrap an Always On Availability Group on Kubernetes. I'm excited to share it today as an open-source project: sql-on-k8s-operator. Let's go. ## Write SQL Your Way: Dual Parameter Style Benefits in mssql-python DevFeed: [Write SQL Your Way: Dual Parameter Style Benefits in mssql-python]() Original publisher: [Read original article]() Author: Jahnvi Thakkar Published: 2026-04-07T16:12:05Z Content type: article Language: en Sources: [Microsoft Python Engineering]() Topics: [sql-server](), [Python](), [SQL](), [Microsoft](), [Azure]() Tags: [azure](), [azure-sql](), [client-driver](), [code](), [developers](), [microsoft](), [python](), [python-driver-for-azure-sql](), [python-driver-for-sql-server](), [sql](), [sql-server](), [sql-server-2025]() ### AI overview Microsoft's mssql-python driver now supports both qmark positional parameters and pyformat named parameters for Python applications using SQL Server and Azure SQL. The driver automatically detects the parameter style from the supplied tuple, list, or dictionary, while preserving existing qmark code without configuration changes. ### Source excerpt Reviewed by: Sumit Sarabhai If you've been writing SQL in Python, you already know the debate: positional parameters (?) or named parameters (%(name)s)? Some developers swear by the conciseness of positional. Others prefer the clarity of named. With mssql-python, you no longer need to choose - we support both. We've added dual parameter style support to mssql-python, enabling both qmark and pyformat parameter styles in Python [...] The post Write SQL Your Way: Dual Parameter Style Benefits in mssql-python appeared first on Microsoft for Python Developers Blog. ## MOLT: A Toolkit for Migrations You Can Trust DevFeed: [MOLT: A Toolkit for Migrations You Can Trust]() Original publisher: [Read original article]() Author: Becca Weng Published: 2026-01-21T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [migration](), [CockroachDB](), [Databases](), [Replication](), [Scalability](), [Parsing]() Tags: [cockroachdb](), [database](), [distributed](), [insights](), [migrations](), [mysql](), [oracle](), [postgres](), [scalability](), [sql-server](), [tools]() ### AI overview This article presents Cockroach Labs' MOLT toolkit for migrating databases to CockroachDB. It describes schema conversion, bulk data transfer, verification, and live replication as parts of a modular migration workflow. ### Source excerpt Migrating a database is always a high-stakes operation. Downtime, data correctness, data loss, and customer experience are all on the line. Not to mention the business risk if a migration goes poorly. While there are a number of third-party tools that support data migration to CockroachDB, we have the expertise and insights into our product. We knew we could make migrations as efficient as possible in-house. ## Comparing Integers and Doubles DevFeed: [Comparing Integers and Doubles]() Original publisher: [Read original article]() Author: Thomas Neumann (noreply@blogger.com) Published: 2025-11-10T16:55:00Z Content type: article Language: en Sources: [Database Architects]() Topics: [floating-point](), [SQL](), [DuckDB](), [sql-server](), [Programming](), [C++]() Tags: [c-plus-plus](), [compiler](), [duckdb](), [floating-point](), [precision](), [sql](), [sql-server](), [testing](), [undefined-behavior]() ### AI overview The article explains how comparing large integers with double-precision values can lose integer precision and produce non-transitive results in SQL systems. It describes how this can cause differences between ordinary comparisons and hash joins, and outlines a conversion-based approach for correct comparisons. ### Source excerpt During automated testing we stumbled upon a problem that boiled down to transitive comparisons: If a=b, and a=c, when we assumed that b=c. Unfortunately that is not always the case, at least not in all systems. Consider the following SQL query: select a=b, a=c, b=c from (values( 1234567890123456789.0::double precision, 1234567890123456788::bigint, 1234567890123456789::bigint)) s(a,b,c) If you execute that in Postgres (or DuckDB, or SQL Server, or ...) the answer is (true, true, false). That is, the comparison is not transitive! Why does that happen? When these systems compare a bigint and a double, they promote the bigint to double and then compare. But a double has only 52 bits of mantissa, which means it will lose precision when promoting large integers to double, producing false positives in the comparison. This behavior is highly undesirable, first because it confuses the optimizer, and second because (at least in our system) joins work very differently: Hash joins promote to the most restrictive type and discard all values that cannot be represented, as they will never produce a join partner for sure. For double/bigint joins that leads to observable differences between joins and plain comparisons, which is very bad. How should we compare correctly? Conceptually the situation is clear, an IEEE 754 floating point with sign s, mantissa m, and exponent e represents the values (-1)^s*m*2^e, we just have to compare the integer with that value. But there is no easy way to do that, if we do a int/double comparison in, e.g., C++, the compiler does the same promotion to double, messing up the comparison. We can get the logic right by doing two conversions: We first convert the int to double and compare that. If the values are not equal, the order is clear and we can use that. Otherwise, we convert the double back to an integer and check if the conversion rounded up or down, and handle the result. Plus some extra checks to avoid undefined behavior (the conversion of intma ## Simplifying Resource Management in mssql-python through Context Manager DevFeed: [Simplifying Resource Management in mssql-python through Context Manager]() Original publisher: [Read original article]() Author: Jahnvi Thakkar Published: 2025-09-26T09:49:51Z Content type: tutorial Language: en Sources: [Microsoft Python Engineering]() Topics: [Python](), [sql-server](), [Databases](), [Exception]() Tags: [azure](), [azure-sql](), [cleanup](), [client-driver](), [databases](), [exception-handling](), [python](), [python-driver-for-azure-sql](), [python-driver-for-sql-server](), [sql-server](), [sql-server-2025](), [transactions]() ### AI overview This tutorial explains context manager support in the mssql-python driver for Python applications using SQL Server and Azure SQL. It describes how context managers manage connections and cursors, commit successful transactions, roll back transactions when exceptions occur, and close connections automatically. ### Source excerpt Reviewed by: Sumit Sarabhai and Gaurav Sharma If you've worked with databases in Python, you know the boilerplate: open a connection, create a cursor, run queries, commit or rollback transactions, close cursors and connection. Forgetting just one cleanup step can lead to resource leaks (open connections) or even inconsistent data. That's where context managers step [...] The post Simplifying Resource Management in mssql-python through Context Manager appeared first on Microsoft for Python Developers Blog. ## Think About SQL MERGE in Terms of a RIGHT JOIN DevFeed: [Think About SQL MERGE in Terms of a RIGHT JOIN]() Original publisher: [Read original article]() Author: lukaseder Published: 2025-03-13T14:45:53Z Content type: tutorial Language: en Sources: [jOOQ]() Topics: [SQL](), [etl](), [rdbms]() Tags: [databricks](), [etl](), [firebird](), [merge](), [outer-join](), [postgresql](), [right-join](), [schema](), [semantics](), [source](), [sql](), [sql-server](), [statement](), [syntax](), [table](), [target-table](), [when-matched](), [when-not-matched](), [when-not-matched-by-source]() ### AI overview The article explains SQL MERGE by relating its target-and-source behavior to a RIGHT JOIN. It covers updating matching rows, inserting nonmatching rows, deletion behavior, and the restriction against duplicate matches. ### Source excerpt RIGHT JOIN is an esoteric feature in the SQL language, and hardly ever seen in the real world, because almost every RIGHT JOIN can just be expressed as an equivalent LEFT JOIN. The following two statements are equivalent: It's not unreasonable to expect these two statements to produce the same execution plan on most RDBMS, ... Continue reading Think About SQL MERGE in Terms of a RIGHT JOIN -> ## An Efficient Way to Check for Existence of Multiple Values in SQL DevFeed: [An Efficient Way to Check for Existence of Multiple Values in SQL]() Original publisher: [Read original article]() Author: lukaseder Published: 2024-02-16T14:16:45Z Content type: tutorial Language: en Sources: [jOOQ]() Topics: [SQL](), [Benchmark](), [Oracle Database](), [PostgreSQL]() Tags: [benchmark](), [benchmarking](), [compare](), [count](), [database](), [derived-table](), [execution](), [exists](), [join](), [limit](), [mysql](), [oracle](), [oracle-23c](), [performance](), [postgresql](), [rdbms](), [sql](), [sql-performance](), [sql-server](), [sql-syntax](), [top]() ### AI overview This article explains how to check whether multiple matching rows exist in SQL. It recommends limiting rows in a derived table before counting them, then compares execution plans and benchmark results for PostgreSQL 15 and Oracle 23c. ### Source excerpt In a previous blog post, we've advertised the use of SQL EXISTS rather than COUNT(*) to check for existence of a value in SQL. I.e. to check if in the Sakila database, actors called WAHLBERG have played in any films, instead of: Do this: (Depending on your dialect you may require a FROM DUAL clause, ... Continue reading An Efficient Way to Check for Existence of Multiple Values in SQL -> ## Can Debezium Lose Events? DevFeed: [Can Debezium Lose Events?]() Original publisher: [Read original article]() Published: 2023-11-14T14:00:00Z Content type: article Language: en Sources: [Gunnar Morling]() Topics: [data observability](), [Replication](), [Database](), [configuration](), [MySQL](), [Amazon RDS]() Tags: [amazon-rds](), [configuration](), [data-engineering](), [database](), [disk-space](), [mysql](), [replication](), [sql-server]() ### AI overview The article explains that Debezium should generally not miss database change events because its delivery semantics are at-least-once. Event loss can occur when operational issues cause required transaction-log data to be discarded before a connector captures it, such as when retention limits are exceeded during extended downtime. It discusses retention behavior for MySQL, Amazon RDS, SQL Server, and PostgreSQL replication slots. ### Source excerpt This question came up on the Data Engineering sub-reddit the other day: Can Debezium lose any events? I.e. can there be a situation where a record in a database get inserted, updated, or deleted, but Debezium fails to capture that event from the transaction log and propagate it to downstream consumers? ## 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 -> ## Application Security Roundup - Feb DevFeed: [Application Security Roundup - Feb]() Original publisher: [Read original article]() Author: Adam Published: 2023-02-27T00:00:00Z Content type: article Language: en Sources: [Shostack & Friends Blog]() Topics: [Application Security](), [Memory Safety](), [Microsoft](), [Android](), [Linux](), [C++](), [Azure SQL](), [sql-server]() Tags: [android](), [application-security](), [azure-sql](), [c-plus-plus](), [linux](), [memory-safety](), [microsoft](), [security](), [sql-server]() ### AI overview This February application security roundup focuses on memory safety, including progress and commentary involving Microsoft, Google, Apple, Linux, Android 13, and ISO C++. It also covers AppSec Dublin trip reports, Azure variant hunting, and repudiation threats in Azure SQL Database and SQL Server. ### Source excerpt This month is all about memory safety, unless you're a standards group. ## LATERAL is Your Friend to Create Local Column Variables in SQL DevFeed: [LATERAL is Your Friend to Create Local Column Variables in SQL]() Original publisher: [Read original article]() Author: lukaseder Published: 2022-11-04T08:56:17Z Content type: tutorial Language: en Sources: [jOOQ]() Topics: [SQL](), [Databases]() Tags: [apply](), [cross-apply](), [cross-join-lateral](), [derived-table](), [examples](), [lateral](), [lateral-derived-table](), [local-variables](), [oracle](), [outer-apply](), [postgresql](), [sql](), [sql-server](), [variables]() ### AI overview This article explains how SQL's LATERAL clause can be used to define local column variables next to the tables that provide their values. It compares this approach with derived tables and notes database-specific syntax, including SQL Server's CROSS APPLY. ### Source excerpt The standard SQL WITH clause has been tremendously helpful in structuring SQL queries. Instead of nesting everything in unreadable derived tables like this: People have started moving the logic up front, just like in any other programming language, where we declare things first, lexically, then use them: Both queries will produce the 5 actors with ... Continue reading LATERAL is Your Friend to Create Local Column Variables in SQL -> ## Calling Procedures with Default Parameters using JDBC or jOOQ DevFeed: [Calling Procedures with Default Parameters using JDBC or jOOQ]() Original publisher: [Read original article]() Author: lukaseder Published: 2022-10-21T14:35:39Z Content type: tutorial Language: en Sources: [jOOQ]() Topics: [Code](), [Reason](), [SQL](), [Oracle Database](), [PostgreSQL]() Tags: [db2](), [default-parameters](), [java](), [jdbc](), [jooq](), [jooq-in-use](), [oracle](), [pl-pgsql](), [pl-sql](), [postgresql](), [sql-server](), [stored-functions](), [stored-procedures](), [syntax]() ### AI overview This tutorial explains how to call stored procedures with default parameters using JDBC or jOOQ. It shows how directly instantiating a procedure call allows Java code to omit parameters that have database-side defaults, and notes that syntax varies across supported relational database systems. ### Source excerpt Using jOOQ's code generator to call stored procedures is a popular reason to use jOOQ. For example, when you have a procedure like the following Oracle PL/SQL procedure: jOOQ will generate code for you to call very simply, like this: This will execute the following, taking care of binding all IN and OUT parameters for ... Continue reading Calling Procedures with Default Parameters using JDBC or jOOQ -> ## Pre-Conference Workshop and Sessions at PASS Summit DevFeed: [Pre-Conference Workshop and Sessions at PASS Summit]() Original publisher: [Read original article]() Author: Anthony Nocentino Published: 2022-10-16T14:13:18Z Content type: news Language: en Sources: [Kubernetes on Anthony Nocentino's Blog]() Topics: [pass](), [Cloud](), [Azure](), [Kubernetes](), [SQL](), [sql-server](), [data](), [Deployment](), [Disaster Recovery](), [Availability](), [Microsoft]() Tags: [announce](), [availability](), [azure](), [azure-arc](), [cloud](), [community](), [conference](), [data](), [disaster-recovery](), [kubernetes](), [linux](), [microsoft](), [sql](), [sql-server](), [training]() ### AI overview The author announces three presentations at PASS Data Community Summit 2022: a pre-conference workshop on designing hybrid cloud strategies, a regular session on cloud data infrastructure, and a Learning Path session. ### Source excerpt I'm pleased to announce that I will be presenting at this year's PASS Summit. PASS Data Community Summit 2022 is the year's largest gathering of data platform professionals in the US. This year I have a pre-conference workshop, a regular session, and a Learning Path session. Let's dive into each. Pre-Conference Workshop: Become a Hybrid Architect My good friend Ben E. Weissman and I will teach a pre-conference workshop called "Become a Hybrid Architect" in this workshop we will cover the foundations needed to design and build a hybrid cloud strategy for your organization. ## How to Connect to Microsoft SQL Server Remotely Using Teleport DevFeed: [How to Connect to Microsoft SQL Server Remotely Using Teleport]() Original publisher: [Read original article]() Author: travis.rodgers@goteleport.com (Travis Rodgers) Published: 2022-09-20T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [sql-server](), [active directory](), [audit](), [Authentication](), [Security](), [Firewall](), [VPC]() Tags: [active-directory](), [audit](), [authentication](), [firewall](), [how-to](), [security](), [sql-server](), [vpc]() ### AI overview This tutorial explains how to connect to Microsoft SQL Server remotely using Teleport and Active Directory authentication. It recommends Windows authentication, limiting public exposure through network isolation, and enabling auditing for logins, sessions, and SQL queries. ### Source excerpt In this blog post, we'll look at how to connect to Microsoft SQL Server remotely using Teleport and Active Directory Authentication. ## Using H2 as a Test Database Product with jOOQ DevFeed: [Using H2 as a Test Database Product with jOOQ]() Original publisher: [Read original article]() Author: lukaseder Published: 2022-08-19T07:25:43Z Content type: tutorial Language: en Sources: [jOOQ]() Topics: [in-memory database](), [Testing](), [Java](), [SQL](), [sql-server]() Tags: [compatibility-mode](), [database](), [h2](), [in-memory-database](), [integration-testing](), [java](), [jooq](), [jooq-in-use](), [sql](), [sql-server](), [testcontainers](), [testing](), [vendor-agnosticity]() ### AI overview This article explains the trade-offs of using H2 as a test database for Java applications with jOOQ. It shows why SQL that works on H2 may require syntax changes on SQL Server, describes H2 compatibility modes, and notes that jOOQ generates SQL for H2's native dialect rather than its compatibility modes. ### Source excerpt The H2 database is an immensely popular in-memory database product mostly used by Java developers for testing. If you check out the DB-Engines ranking, it ranks 50th, which is quite impressive, as this rank outperforms products like: CockroachDB Ignite Single Store (previously MemSQL) Interbase (which was forked as Firebird) Ingres (which is a predecessor to ... Continue reading Using H2 as a Test Database Product with jOOQ -> ## Securing Microsoft SQL Server DevFeed: [Securing Microsoft SQL Server]() Original publisher: [Read original article]() Author: info@goteleport.com (Kainaat Arshad) Published: 2022-07-22T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [sql-server](), [Security](), [Vulnerabilities]() Tags: [best-practices](), [compliance](), [hardening](), [security](), [sql-server](), [vulnerabilities]() ### AI overview An overview of standard practices for securing and hardening Microsoft SQL Server deployments across network, transport, and database levels. It explains risks including weak default settings, SQL injection, denial-of-service attacks, verbose error messages, and compliance gaps. ### Source excerpt An overview of best practices for securing and hardening MS SQL deployments. ## The Performance of Various To-Many Nesting Algorithms DevFeed: [The Performance of Various To-Many Nesting Algorithms]() Original publisher: [Read original article]() Author: lukaseder Published: 2022-06-09T10:15:50Z Content type: article Language: en Sources: [jOOQ]() Topics: [Benchmark](), [SQL](), [Databases](), [Object-relational mapping]() Tags: [benchmark](), [benchmarks](), [database](), [java](), [jooq](), [jooq-development](), [json-arrayagg](), [many-to-many](), [multiset](), [mysql](), [nested-collections](), [one-to-many](), [oracle](), [ordbms](), [performance](), [postgresql](), [sql](), [sql-json](), [sql-server](), [sql-xml](), [test-data]() ### AI overview This article benchmarks several approaches to nesting to-many relationships with jOOQ, including MULTISET emulation, single joins with client-side deduplication, and multiple queries per nesting level. It reports that these approaches outperform the N+1 approach, with relative performance depending on data size and use case. ### Source excerpt It's been a while since jOOQ 3.15 has been released with its revolutionary standard SQL MULTISET emulation feature. A thing that has been long overdue and which I promised on twitter a few times is to run a few benchmarks comparing the performance of various approaches to nesting to-many relationships with jOOQ. This article will ... Continue reading The Performance of Various To-Many Nesting Algorithms -> ## Intro to SQL for the New Grad Developer DevFeed: [Intro to SQL for the New Grad Developer]() Original publisher: [Read original article]() Author: Brandon Raboy Published: 2022-06-08T13:00:00Z Content type: tutorial Language: en Sources: [Nic Raboy]() Topics: [SQL](), [Databases](), [MySQL](), [Oracle Database](), [PostgreSQL](), [sql-server]() Tags: [databases](), [developer](), [guide](), [mysql](), [oracle](), [postgresql](), [rdbms](), [sql](), [sql-server](), [syntax]() ### AI overview A beginner-oriented guide to SQL for new graduate developers. It explains SQL's role in accessing and manipulating databases, surveys MySQL, PostgreSQL, Oracle, and SQL Server, and introduces syntax differences, EXPLAIN, query runtime, and example problems. ### Source excerpt Ever since studying and working with databases 6 months ago, I've become fascinated with SQL and its relatively simple syntax. As a guide to the reader, I've gathered the essential criteria that emplo... The post Intro to SQL for the New Grad Developer appeared first on The Polyglot Developer. [Next page]()