# R2DBC Published articles for R2DBC. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## jOOQ 3.20 released with ClickHouse, Databricks, and much more DuckDB support, new modules, Oracle type hierarchies, more spatial support, decfloat and synonym support, hidden columns, Scala 3, Kotlin 2, and much more DevFeed: [jOOQ 3.20 released with ClickHouse, Databricks, and much more DuckDB support, new modules, Oracle type hierarchies, more spatial support, decfloat and synonym support, hidden columns, Scala 3, Kotlin 2, and much more]() Original publisher: [Read original article]() Author: lukaseder Published: 2025-02-20T10:27:54Z Content type: release Language: en Sources: [jOOQ]() Topics: [clickhouse](), [databricks](), [SQL](), [DuckDB](), [modules](), [Oracle Database](), [Kotlin](), [Scala](), [reactive](), [jpa]() Tags: [array](), [clickhouse](), [databricks](), [decfloat](), [dirty-tracking](), [dml-join](), [duckdb](), [hidden-columns](), [jdk-21](), [jooq](), [jooq-3-20](), [jooq-development](), [jpa](), [json](), [kotlin](), [kotlin-2](), [merge](), [modules](), [oracle](), [oracle-plsql-types](), [r2dbc](), [reactive](), [scala](), [scala-3](), [sequences](), [spatial](), [sql]() ### AI overview jOOQ 3.20 introduces experimental ClickHouse and Databricks SQL dialects, improves DuckDB support, adds new integration modules, and expands support for Oracle type hierarchies, spatial features, decfloat, synonyms, hidden columns, Scala 3, and Kotlin 2. ### Source excerpt New dialects: jOOQ 3.20 ships with 2 new experimental dialects: ClickHouse is a fast-moving SQL dialect with a historic vendor-specific syntax that is gradually migrated to a more standards compliant alternative, which is why our support is still experimental. A lot of behaviours differ from what one would expect elsewhere, including NULL handling, which is ... Continue reading jOOQ 3.20 released with ClickHouse, Databricks, and much more DuckDB support, new modules, Oracle type hierarchies, more spatial support, decfloat and synonym support, hidden columns, Scala 3, Kotlin 2, and much more -> ## 3.18.0 Release with Support for more Diagnostics, SQL/JSON, Oracle Associative Arrays, Multi dimensional Arrays, R2DBC 1.0 DevFeed: [3.18.0 Release with Support for more Diagnostics, SQL/JSON, Oracle Associative Arrays, Multi dimensional Arrays, R2DBC 1.0]() Original publisher: [Read original article]() Author: lukaseder Published: 2023-03-08T16:34:56Z Content type: release Language: en Sources: [jOOQ]() Topics: [releases](), [SQL](), [JSON](), [Oracle Database](), [PostgreSQL](), [Kotlin]() Tags: [jdbc](), [jooq](), [kotlin](), [oracle](), [r2dbc](), [release](), [sql](), [sql-json](), [uncategorized]() ### AI overview jOOQ 3.18.0 is a release focused on expanded SQL diagnostics and SQL/JSON support, including vendor-specific MySQL and PostgreSQL features. It also adds improvements for the Query Object Model, Oracle associative arrays, PostgreSQL multidimensional arrays, Kotlin, and R2DBC 1.0. ### Source excerpt DiagnosticsListener improvements A lot of additional diagnostics have been added, including the automated detection of pattern replacements, helping you lint your SQL queries irrespective of whether you're using jOOQ to write your SQL, or if you're using it as a JDBC / R2DBC proxy for an existing application. A lot of these diagnostics are available ... Continue reading 3.18.0 Release with Support for more Diagnostics, SQL/JSON, Oracle Associative Arrays, Multi dimensional Arrays, R2DBC 1.0 -> ## How to use jOOQ's Converters with UNION Operations DevFeed: [How to use jOOQ's Converters with UNION Operations]() Original publisher: [Read original article]() Author: lukaseder Published: 2023-03-02T11:18:17Z Content type: tutorial Language: en Sources: [jOOQ]() Topics: [SQL](), [Databases]() Tags: [ad-hoc-converter](), [converter](), [how-to](), [jdbc](), [jooq](), [jooq-in-use](), [lambda](), [multiset](), [r2dbc](), [rdbms](), [sql](), [union]() ### AI overview This tutorial explains how jOOQ ad-hoc converters behave with UNION operations. Because conversion occurs on the client after JDBC retrieval, it does not affect server-side UNION processing, and jOOQ applies the result-fetching row type from the first subquery. The article recommends applying client-side conversions consistently across subqueries or moving the conversion to the server when appropriate. ### Source excerpt jOOQ 3.15 introduced the concept of an ad-hoc converter, a converter that is applied "ad-hoc" to a single query. It uses the same underlying mechanisms as any ordinary Converter that is attached to generated code for use in every query. An example of such an ad-hoc converter is this: While there are other ways to ... Continue reading How to use jOOQ's Converters with UNION Operations -> ## Why You Should Execute jOOQ Queries With jOOQ DevFeed: [Why You Should Execute jOOQ Queries With jOOQ]() Original publisher: [Read original article]() Author: lukaseder Published: 2023-01-18T11:46:25Z Content type: opinion Language: en Sources: [jOOQ]() Topics: [SQL](), [Java](), [Databases](), [Compiler]() Tags: [code-generation](), [crud](), [csv](), [execution](), [export](), [identity](), [import](), [java](), [jdbc](), [jooq](), [jooq-in-use](), [jpa](), [json](), [mapping](), [multiset](), [nested-collections](), [nested-records](), [orm](), [r2dbc](), [sql](), [stored-procedures](), [type-safety](), [udt](), [updatablerecord](), [user-defined-types](), [xml]() ### AI overview The article argues that queries built with jOOQ should generally also be executed with jOOQ. It explains that jOOQ preserves type safety and structured result mapping during execution, whereas extracting SQL and bind values for JDBC-level execution loses compiler knowledge of the result set. It acknowledges limited use cases for executing jOOQ-generated SQL elsewhere, such as a small number of dynamic queries in an otherwise JPA-based application. ### Source excerpt Previously on this blog, I've written a post explaining why you should use jOOQ's code generator, despite the possibility of using jOOQ without it. In a similar fashion, as I've answered numerous jOOQ questions on Stack Overflow, where someone used jOOQ to build a query, but then executed it elsewhere, including on: jOOQ itself isn't ... Continue reading Why You Should Execute jOOQ Queries With jOOQ -> ## jOOQ's R2DBC LoggingConnection to log all SQL statements DevFeed: [jOOQ's R2DBC LoggingConnection to log all SQL statements]() Original publisher: [Read original article]() Author: lukaseder Published: 2023-01-17T10:12:05Z Content type: article Language: en Sources: [jOOQ]() Topics: [SQL](), [reactive](), [Code]() Tags: [code](), [dependency](), [hibernate](), [jdbc](), [jdbctemplate](), [jooq](), [jooq-in-use](), [logging](), [native](), [r2dbc](), [reactive](), [sql]() ### AI overview The article introduces jOOQ's LoggingConnection for R2DBC clients, which logs reactive SQL queries. It notes that the utility is available in jOOQ versions 3.18.0, 3.17.7, and 3.16.13, and that standalone code is available on GitHub. ### Source excerpt jOOQ already has a LoggingConnection (see also the manual), which acts as a JDBC proxy Connection to log all SQL statements that are executed by any JDBC client (including Hibernate, MyBatis, JdbcTemplate, native JDBC, etc.). Starting from jOOQ 3.18.0, 3.17.7, and 3.16.13, a LoggingConnection is now also available for R2DBC clients to log all reactive ... Continue reading jOOQ's R2DBC LoggingConnection to log all SQL statements -> ## A Brief Overview over the Most Common jOOQ Types DevFeed: [A Brief Overview over the Most Common jOOQ Types]() Original publisher: [Read original article]() Author: lukaseder Published: 2022-09-06T12:30:37Z Content type: tutorial Language: en Sources: [jOOQ]() Topics: [SQL](), [API](), [Databases](), [Structured-data]() Tags: [api](), [api-design](), [cheat-sheet](), [configuration](), [context](), [dependency-injection](), [dsl](), [jdbc](), [jooq](), [jooq-3-17](), [jooq-in-use](), [logging](), [overview](), [queryparts](), [r2dbc](), [sql](), [syntax](), [type-system](), [types]() ### AI overview This tutorial provides a cheat sheet of the most important types in the jOOQ API, covering configuration, scopes, settings, and DSL APIs. It notes that jOOQ 3.17 includes more than 160 settings and explains how several type groups support query construction, execution, lifecycle management, and dependency injection. ### Source excerpt For new users working with jOOQ for the first time, the number of types in the jOOQ API can be overwhelming. The SQL language doesn't have many such "visible" types, although if you think about SQL the way jOOQ does, then they're there just the same, but hidden from users via an English style syntax. ... Continue reading A Brief Overview over the Most Common jOOQ Types -> ## 3.17.0 Release with Computed Columns, Audit Columns, Pattern Matching, Reactive Transactions and Kotlin Coroutine Support DevFeed: [3.17.0 Release with Computed Columns, Audit Columns, Pattern Matching, Reactive Transactions and Kotlin Coroutine Support]() Original publisher: [Read original article]() Author: lukaseder Published: 2022-06-22T15:15:05Z Content type: release Language: en Sources: [jOOQ]() Topics: [releases](), [SQL](), [Kotlin](), [reactive](), [Transactions]() Tags: [audit-columns](), [client-side-computed-columns](), [computed-columns](), [coroutine](), [coroutines](), [implicit-join](), [java-17](), [jooq](), [jooq-3-17](), [jooq-development](), [kotlin](), [kotlin-coroutines](), [pattern-matching](), [postgresql](), [r2dbc](), [reactive-programming](), [reactive-transactions](), [release](), [release-notes](), [sql](), [stored](), [stored-computed-column](), [udt](), [virtual](), [virtual-computed-column]() ### AI overview The jOOQ 3.17.0 release adds client-side computed columns for read and write operations, audit columns, pattern-matching SQL transformations, and more implicit JOIN capabilities. It also sets Java 17 as the baseline for the Open Source Edition while commercial distributions continue supporting Java 8 and 11. ### Source excerpt This release contiues the work from previous releases around more sophisticated SQL transformation capabilities, including: Client side computed columns for both read and write operations Audit columns Pattern matching SQL transformations More implicit JOIN capabilities Client side computed columns A ground breaking new core feature available in all commercial distributions isthe new client side computed ... Continue reading 3.17.0 Release with Computed Columns, Audit Columns, Pattern Matching, Reactive Transactions and Kotlin Coroutine Support -> ## The Many Different Ways to Fetch Data in jOOQ DevFeed: [The Many Different Ways to Fetch Data in jOOQ]() Original publisher: [Read original article]() Author: lukaseder Published: 2022-05-19T07:29:09Z Content type: tutorial Language: en Sources: [jOOQ]() Topics: [jooq](), [Java](), [SQL]() Tags: [collections](), [collector](), [convenience](), [fetching](), [java](), [jdbc](), [joo-f6a0c60d3d07](), [jooq](), [jooq-in-use](), [optional](), [r2dbc](), [reactive-streams](), [sql](), [stream-api](), [streams]() ### AI overview This tutorial explains several ways to fetch data with jOOQ, including eager result-set fetching, external and internal iteration, single-record retrieval, optional results, and resource-managed fetching for large data sets. ### Source excerpt The jOOQ API is all about convenience, and as such, an important operation (the most important one?) like fetch() must come with convenience, too. The default way to fetch data is this: It fetches the entire result set into memory and closes the underlying JDBC resources eagerly. But what other options do we have? Iterable ... Continue reading The Many Different Ways to Fetch Data in jOOQ ->