# MySQL MySQL is an open-source relational SQL database management system. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Evaluating LLM models for DBA tasks DevFeed: [Evaluating LLM models for DBA tasks]() Original publisher: [Read original article]() Author: Vadim Tkachenko Published: 2026-09-17T11:50:07Z Content type: article Language: en Sources: [Blog - Percona]() Topics: [LLM evaluation / benchmarking](), [Database](), [Large Language Model](), [MySQL](), [Replication]() Tags: [benchmark](), [database](), [database-administration](), [guardrails](), [harness](), [llm](), [models](), [mysql](), [openrouter](), [replication](), [uncategorized]() ### AI overview This article describes a harness for evaluating open-weight and other LLMs on real database administration tasks performed on remote systems. It reports that most models completed the tasks, while smaller models often achieved similar results at lower cost but required more steps. The article also shows that models may adapt when the requested software version is unavailable, highlighting the need for validation and guardrails. ### Source excerpt Evaluating LLM Models for DBA Tasks Large language models are increasingly capable of performing practical systems-administration tasks. I wanted to understand how well they could handle something more specialized: database administration. To explore this, I developed a harness for evaluating the ability of different LLMs to execute real DBA tasks on remote systems. My ... Continued The post Evaluating LLM models for DBA tasks appeared first on Percona. ## Too many GCache Page Files in MySQL Data Directory DevFeed: [Too many GCache Page Files in MySQL Data Directory]() Original publisher: [Read original article]() Author: Kedar Vaijanapurkar Published: 2026-09-17T05:29:14Z Content type: tutorial Language: en Sources: [Blog - Percona]() Topics: [XtraDB Cluster (PXC)](), [Replication](), [Transactions](), [MySQL]() Tags: [cluster](), [database-administration](), [disk-space](), [galera](), [galera-replication](), [gcache](), [gcache-freeze-purge-at-seqno](), [gcache-keep-pages-count](), [gcache-page](), [gcache-page-files](), [gcache-purge](), [gcache-troubleshooting](), [mysql](), [mysql-disk-space](), [mysql-troubleshooting](), [percona-xtradb-cluster](), [pxc](), [replication](), [xtradb-cluster-pxc]() ### AI overview An investigation into thousands of GCache page files accumulating in a Percona XtraDB Cluster data directory. The article explains how frozen GCache purging caused disk growth, links the behavior to a cluster partition, and describes reproducing it by setting gcache.freeze_purge_at_seqno and generating workload. ### Source excerpt Learn why PXC accumulates thousands of gcache.page.* files, how frozen GCache purging causes disk growth, and how to safely recover and rejoin using IST. The post Too many GCache Page Files in MySQL Data Directory appeared first on Percona. ## Keycloak 26.7.4 released DevFeed: [Keycloak 26.7.4 released]() Original publisher: [Read original article]() Author: Keycloak Team Published: 2026-09-16T00:00:00Z Content type: release Language: en Sources: [Keycloak Blog]() Topics: [Keycloak](), [Security](), [Quarkus](), [MariaDB](), [MySQL](), [saml]() Tags: [cve](), [idm](), [kerberos](), [keycloak](), [keycloak-release](), [ldap](), [mariadb](), [mysql](), [openid-connect](), [quarkus](), [release](), [saml](), [security](), [sso]() ### AI overview Keycloak 26.7.4 was released on September 16, 2026. The release includes security fixes for several CVEs, an upgrade to Quarkus 3.33.3.2, and fixes for performance, testing, documentation, administration, and UI issues. ### Source excerpt To download the release go to Keycloak downloads. Upgrading Before upgrading refer to the migration guide for a complete list of changes. All resolved issues Security fixes #52834 [CVE-2026-90997] Default MySQL/MariaDB row counts make stateless replay gates accept reused artifacts #52835 [CVE-2026-79651] Keycloak Unauthenticated Denial of Service via Unbounded Locale Caching #52836 [CVE-2026-74909] Incomplete fix: percent-encoded semicolon bypasses matrix parameter stripping in PathMatcher #52837 [CVE-2026-19607] Username Takeover Leading to Account Lockout #52838 [CVE-2026-17526] Privilege escalation: the "impersonation" role can impersonate a realm administrator #52839 [CVE-2026-18212] SAML Redirect DEFLATE helpers leak native zlib state Enhancements #52354 Upgrade to Quarkus 3.33.3.2 dist/quarkus Bugs #49635 Performance issue with 26.6.2 dist/quarkus #51102 Flaky test: org.keycloak.testsuite.oauth.AccessTokenTest#accessTokenRequest ci #52015 New links errors for https://quarkus.io/guides docs #52172 Cached `RealmAdapter.isUserManagedAccessAllowed()` returns `isEnabled()` infinispan #52173 `realm_client` is computed into a client's attributes and then persisted on save admin/api #52233 Oracle 19 full client OCI driver crashes on startup since 26.6.0 -- SQLFeatureNotSupportedException on setNetworkTimeout dist/quarkus #52241 Clicking on a sub group in the admin console throws an exception admin/ui #52283 Flaky test SessionRestServiceTest.testGetDevicesSessions testsuite #52430 Flaky test: userprofile.spec.ts fails with timeout on "no-users-found-empty-action" in serial suite testsuite ## Announcing Fedora Linux 45 Beta DevFeed: [Announcing Fedora Linux 45 Beta]() Original publisher: [Read original article]() Author: Aoife Moloney Published: 2026-09-15T14:05:00Z Content type: release Language: en Sources: [Fedora Magazine]() Topics: [Fedora](), [Linux](), [dnf](), [podman](), [pandas](), [Python](), [gcc](), [Go Language](), [MariaDB](), [MySQL](), [Filesystems]() Tags: [2026](), [dnf](), [fedora-project-community](), [filesystems](), [gcc](), [go](), [linux](), [mysql](), [pandas](), [partitioning](), [podman](), [pre-release](), [python](), [release](), [toolchains]() ### AI overview Fedora Linux 45 Beta is available for download or upgrade on September 15, 2026. The release includes changes to the kernel console, package signature verification, desktop secret management, software versions, Atomic Desktop image builds, Fedora CoreOS swap support, Anaconda installation flows, and Stratis filesystem partitioning. ### Source excerpt Fedora Linux 45 Beta is here! On Tuesday, 15 September 2026 you can download or upgrade your systems from your usual spots to start enjoying what F45 has to offer early. How to get the beta release You can download F45 Beta, or our pre-release edition versions, from any of the following places: You can [...] ## Performance improvements in Percona Server 8.4.11-11 DevFeed: [Performance improvements in Percona Server 8.4.11-11]() Original publisher: [Read original article]() Author: Bogdan Degtyariov Published: 2026-09-15T11:52:54Z Content type: article Language: en Sources: [Blog - Percona]() Topics: [Percona Server for MySQL](), [Percona](), [MySQL](), [Cache](), [Scalability](), [Database]() Tags: [benchmark](), [benchmarks](), [cache](), [io](), [mysql](), [percona](), [percona-server-for-mysql](), [performance](), [scalability]() ### AI overview This article describes performance and scalability improvements in Percona Server for MySQL 8.4.11-11, focusing on changes to the InnoDB buffer pool and page flushing. It explains how narrowing mutex coverage and using finer-grained latching allows physical reads to proceed more in parallel, particularly for read-heavy, I/O-bound workloads. ### Source excerpt Focusing on Percona Server 8.4.11-11 My previous post (Performance Progression of Percona Server for MySQL 8.4) did a brief review of the performance changes in Percona Server for MySQL 8.4 released in 2026. I recommend reading it first to better understand the material in this post. Version 8.4.11-11 includes patches that deliver significant improvements in ... Continued The post Performance improvements in Percona Server 8.4.11-11 appeared first on Percona. ## GitHub availability report: August 2026 DevFeed: [GitHub availability report: August 2026]() Original publisher: [Read original article]() Author: Jakub Oleksy Published: 2026-09-10T02:05:17Z Content type: article Language: en Sources: [GitHub Engineering]() Topics: [GitHub](), [site-reliability-engineering](), [migration](), [MySQL](), [GitHub Actions]() Tags: [availability](), [azure](), [company-news](), [database](), [github](), [github-actions](), [github-availability-report](), [migration](), [monitoring](), [mysql](), [news-insights](), [outage](), [performance](), [production]() ### AI overview GitHub reports five August incidents with degraded service performance and describes capacity, resiliency, database, Azure migration, and GitHub Actions improvements. ### Source excerpt In August, we experienced five incidents that resulted in degraded performance across GitHub services. The post GitHub availability report: August 2026 appeared first on The GitHub Blog. ## Loading Parquet data into MySQL with ClickHouse DevFeed: [Loading Parquet data into MySQL with ClickHouse]() Original publisher: [Read original article]() Author: Mark Needham Published: 2026-09-10T00:00:00Z Content type: tutorial Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [MySQL](), [parquet](), [Databases](), [Amazon S3]() Tags: [clickhouse](), [mysql](), [parquet](), [s3](), [sql]() ### AI overview A tutorial on using ClickHouse to load Parquet data into MySQL and query MySQL through ClickHouse table functions. ### Source excerpt Use ClickHouse to load Parquet files into MySQL, explore remote data, and run MySQL queries with table functions and named collections. ## Troubleshoot AWS Advanced JDBC Wrapper configuration for Aurora Global Database write forwarding DevFeed: [Troubleshoot AWS Advanced JDBC Wrapper configuration for Aurora Global Database write forwarding]() Original publisher: [Read original article]() Author: Hema Saminathan Published: 2026-09-03T16:26:20Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [configuration](), [Database](), [MySQL](), [Latency]() Tags: [advanced-300](), [amazon-aurora](), [aws](), [drivers](), [global](), [latency](), [mysql](), [postgresql](), [technical-how-to]() ### AI overview A configuration troubleshooting guide for the AWS Advanced JDBC Wrapper with Aurora Global Database write forwarding. It explains Region-specific settings for primary and secondary Regions, including MySQL-specific write-forwarding behavior. ### Source excerpt Configuring the AWS Advanced JDBC Wrapper for Amazon Aurora Global Database with write forwarding requires Region-specific settings, and misconfiguration causes latency spikes and connection failures. This post walks through the correct dialect, plugins, host patterns, and write forwarding settings for the primary and secondary Regions. ## MySQL CDC connector for ClickPipes is now Generally Available DevFeed: [MySQL CDC connector for ClickPipes is now Generally Available]() Original publisher: [Read original article]() Author: Marta Paes Published: 2026-09-02T14:03:04Z Content type: release Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [MySQL](), [Infrastructure as code](), [Terraform]() Tags: [analytics](), [api](), [clickhouse](), [cloud](), [data](), [infrastructure-as-code](), [mysql](), [observability](), [release](), [terraform]() ### AI overview ClickHouse announces general availability of its MySQL CDC connector for ClickPipes, which replicates MySQL and MariaDB data into ClickHouse Cloud. The release adds automatic parallel snapshotting, reliability and observability improvements, and configuration through the Cloud API and Terraform. ### Source excerpt Replicate MySQL and MariaDB data into ClickHouse Cloud with the generally available MySQL CDC connector, featuring faster parallel snapshots, safer production defaults, improved observability, and infrastructure-as-code support. ## OpenID Connect Authentication for MySQL, Now Fully Open Source DevFeed: [OpenID Connect Authentication for MySQL, Now Fully Open Source]() Original publisher: [Read original article]() Author: Michał Jankowski Published: 2026-09-02T08:56:26Z Content type: article Language: en Sources: [Blog - Percona]() Topics: [MySQL](), [OpenID connect (OIDC)](), [Authentication](), [JSON Web Tokens](), [OAuth](), [Open Source]() Tags: [authentication](), [jwks](), [jwt](), [mysql](), [oauth](), [oauth-2-0](), [oidc](), [open-source](), [openid-connect](), [percona](), [percona-server-for-mysql](), [percona-software](), [security]() ### AI overview Percona Server for MySQL includes an open-source OpenID Connect authentication plugin for specified 8.4 and 9.7 releases. The article explains how it authenticates users through standards-compliant identity providers and describes capabilities beyond the MySQL Enterprise plugin, including JWKS signing-key synchronization, group-to-role mapping, and proxy-user support. ### Source excerpt Percona Server for MySQL now ships with a fully open source OpenID Connect (OIDC) authentication plugin, available starting with Percona Server for MySQL 8.4.11-11 and 9.7.2-2 (not yet released as of this writing). It allows a MySQL account to authenticate against any standards-compliant Identity Provider (IdP) instead of relying on a locally stored password, closing ... Continued The post OpenID Connect Authentication for MySQL, Now Fully Open Source appeared first on Percona. ## How INTEGER and INT Produced Different Schemas in Debezium DevFeed: [How INTEGER and INT Produced Different Schemas in Debezium]() Original publisher: [Read original article]() Author: Prathit Malik Published: 2026-09-02T07:02:02Z Content type: article Language: en Sources: [Grofers]() Topics: [MySQL](), [migration](), [Streaming](), [Kafka](), [SQL](), [Databases]() Tags: [big-data](), [blinkit](), [change](), [database](), [debezium](), [jdbc](), [kafka](), [migration](), [mysql](), [open-source](), [schema](), [sql](), [streaming]() ### AI overview This article investigates a Debezium CDC pipeline failure caused by MySQL INT and INTEGER synonyms being treated as different types. The resulting schema mismatch produced an Integer where a downstream consumer expected a Long, causing a ClassCastException on every batch. It explains how streaming and snapshot schema handling differ and how routine migrations exposed the problem. ### Source excerpt A Debezium investigation: how MySQL synonyms INT and INTEGER were treated as different types. One of our CDC pipelines started failing with a ClassCastException on every batch. java.lang.ClassCastException: class java.lang.Integer cannot be cast to class java.lang.Long The pipeline was producing an Integer, but the downstream consumer expected a Long. Every run failed in the same way, which pointed us toward a schema mismatch rather than an issue with individual records. Background: how CDC works To see why a mismatch like that can hide for years, it helps to know how CDC actually works. Most companies replicate their transactional database (MySQL, Postgres, something similar) into a separate data lake for analytics, rather than querying the source directly, and Change Data Capture (CDC) is what keeps that copy in sync: it tails the database's transaction log and replays every insert, update, and delete downstream. Debezium is the most widely used open-source CDC tool for MySQL, and it builds a table's schema in one of two ways that are supposed to agree but do not always. Streaming mode: the first time it sees a CREATE TABLE or ALTER TABLE in the binlog, it parses the raw SQL text and writes the result to its own internal Kafka topic, database.history.kafka.topic. Every restart after that rebuilds the in-memory schema by replaying that topic, not by re-reading the binlog. Snapshot mode: reads the table definition fresh through MySQL's JDBC metadata interface, which normalizes types, every time it runs. Schema Registry sits downstream of both: each connector writes whatever schema it built into the registry, but neither connector reads its own schema back from it. Keep that in mind; it matters later. The trigger: a routine migration With that in mind, here's what actually happened to us. Rewind two years: one of our upstream service teams added a few columns to a source table as part of a standard schema change. ALTER TABLE ADD COLUMN length double NU ## Announcing native MySQL databases: Bring your MySQL workloads to Appwrite DevFeed: [Announcing native MySQL databases: Bring your MySQL workloads to Appwrite]() Original publisher: [Read original article]() Author: Jake Barnby Published: 2026-09-02T00:00:00Z Content type: release Language: en Sources: [Appwrite Blog]() Topics: [Appwrite](), [MySQL](), [Databases](), [Provisioning](), [Availability](), [Replication](), [autoscaling](), [TLS (Transport Layer Security)]() Tags: [announcements](), [autoscaling](), [availability](), [database](), [databases](), [mysql](), [provisioning](), [replication](), [tls]() ### AI overview Appwrite announces native managed MySQL databases that can run inside the same project as an application's existing backend. The service supports MySQL 8.4 and 8.0, standard drivers and ORMs, TLS, backups and point-in-time recovery, replicas with automatic failover, database branches, scaling, and connection pooling. ### Source excerpt Provision a managed MySQL 8.4 instance inside your Appwrite project and keep using the drivers, ORMs, and tools your applications already depend on. ## Announcing Appwrite 2.0: a new foundation for your apps DevFeed: [Announcing Appwrite 2.0: a new foundation for your apps]() Original publisher: [Read original article]() Author: Eldad Fux Published: 2026-08-31T00:00:00Z Content type: release Language: en Sources: [Appwrite Blog]() Topics: [Appwrite](), [Databases](), [Amazon S3](), [OAuth](), [Firewall](), [MySQL](), [PostgreSQL]() Tags: [feature](), [firewall](), [mysql](), [oauth](), [postgresql](), [products](), [release](), [s3]() ### AI overview Appwrite 2.0 is a major platform release with a new engine, rebuilt Console, relational, schemaless, and vector data support, native PostgreSQL and MySQL engines, S3-addressable storage, OAuth 2.1 and OpenID Connect support, and organization-level Domains and Firewall. ### Source excerpt Appwrite 2.0 brings a new engine, a rebuilt Console, five database types, an S3 API, an OAuth 2.1 server, and organization-level Domains and Firewall. ## 【kube-apiserver】选型收束与开放问题：排除树、Kine 与 events 分集群 DevFeed: [【kube-apiserver】选型收束与开放问题：排除树、Kine 与 events 分集群]() Original publisher: [Read original article]() Author: Liao Tonglang Published: 2026-08-28T00:00:00Z Content type: tutorial Language: zh Sources: [土法炼钢 - 系统与基础设施]() Topics: [Kubernetes](), [Caching](), [etcd](), [SQL](), [MySQL](), [PostgreSQL](), [SQLite](), [Raft]() Tags: [apiserver](), [churn](), [distributed](), [errcompacted](), [etcd](), [events](), [exclusion-tree](), [kine](), [kubernetes](), [mysql](), [open-questions](), [postgresql](), [quota](), [raft](), [selection](), [sql](), [sqlite](), [storage](), [ttl](), [v1-30-3](), [watch-cache]() ### AI overview This concluding article presents a mechanism-based decision tree for diagnosing Kubernetes control-plane issues across kube-apiserver and etcd layers. It explains Kine's differing Watch semantics when using SQLite, PostgreSQL, or MySQL backends, discusses routing Kubernetes Events to a separate etcd cluster, and identifies open questions around watch-cache SLOs, compaction, linear reads, and Lease fencing. ### Source excerpt 用机制排除树收束何时查 apiserver 轴、何时穿透 etcd 轴、何时两轴联查；回收 etcd/13 写下的 apiserver 停损线；Kine SQL backend 的 Watch 语义差与 Jepsen 覆盖空白；events --etcd-servers-overrides 分集群运维；列出 watch cache SLO 联合模型、线性读期望与 Lease+fencing 全链路三个开放问题；以 ADR 语言关闭系列边界。 ## Performance Progression of Percona Server for MySQL 8.4 DevFeed: [Performance Progression of Percona Server for MySQL 8.4]() Original publisher: [Read original article]() Author: Bogdan Degtyariov Published: 2026-08-27T13:07:20Z Content type: article Language: en Sources: [Blog - Percona]() Topics: [MySQL](), [benchmarking](), [Benchmark](), [Scalability](), [configuration](), [cpu](), [Hardware]() Tags: [2026](), [benchmark](), [benchmarking](), [benchmarks](), [concurrency](), [configuration](), [cpu](), [data](), [database](), [hardware](), [intel](), [latency](), [load](), [measurement](), [mysql](), [percona](), [percona-server-for-mysql](), [performance](), [processors](), [run]() ### AI overview This article investigates read/write performance changes across Percona Server for MySQL 8.4 versions released in 2026. It describes benchmark scope, database and buffer-size combinations, configuration, and CPU-frequency controls, while excluding features, security patches, latency percentiles, and resource-utilization measurements. ### Source excerpt 1. Purpose and scope This performance investigation aims to look into the read/write performance of Percona Server for MySQL 8.4 and how it changed between versions released in 2026: 8.4.8-8 released on 12 March 2026 8.4.10-10 released on 30 June 2026 8.4.11-11 released on 20 August 2026 We want to see if there are improvements ... Continued The post Performance Progression of Percona Server for MySQL 8.4 appeared first on Percona. ## Soft deletes affect database constraints, indexes, and application queries DevFeed: [Soft deletes affect database constraints, indexes, and application queries]() Original publisher: [Read original article]() Author: hello@ankit-rana.com Published: 2026-08-20T00:00:00Z Content type: opinion Language: en Sources: [Ankit Rana | Mechanical Sympathy]() Topics: [data-processing](), [Database](), [MySQL]() Tags: [data-modelling](), [database-design](), [foreign-keys](), [indexes](), [indexing](), [mysql](), [orm](), [postgresql](), [predicate](), [schema](), [schema-design](), [soft-delete]() ### AI overview The article explains how soft deletion affects database design beyond adding a deleted_at column. It discusses duplicate-key failures, foreign-key behavior, queries that may return deleted rows, and index inefficiency, noting that PostgreSQL partial indexes help while MySQL requires a workaround. ### Source excerpt A deleted_at column turns every future query into a conditional one, and the cost is not the extra predicate. Unique constraints stop working because the deleted row still occupies the key, foreign keys start pointing at rows the application considers gone, and any query written by someone who does not know about the column silently returns deleted data. Soft delete is a data lifecycle decision, and treating it as a boolean column is what makes it expensive. ## Why your index is not being used, and why the planner is usually right DevFeed: [Why your index is not being used, and why the planner is usually right]() Original publisher: [Read original article]() Author: hello@ankit-rana.com Published: 2026-08-16T00:00:00Z Content type: tutorial Language: en Sources: [Ankit Rana | Mechanical Sympathy]() Topics: [Query (disambiguation)](), [MySQL](), [bug]() Tags: [bug](), [cardinality](), [database-performance](), [explain](), [function](), [indexes](), [indexing](), [mysql](), [postgresql](), [predicate](), [query](), [query-planner]() ### AI overview This tutorial explains why database indexes may not be used even when they exist. It focuses on inaccurate cardinality estimates caused by stale statistics, predicates that prevent index matching, implicit casts, and cases where sequential scans are the cheaper choice. ### Source excerpt An unused index is almost never a planner bug. It is usually a predicate the planner cannot match to the index, such as a function or an implicit cast applied to the column, or a cardinality estimate that is wrong because statistics are stale. When the estimate is right and the planner still refuses, it is often correct: past a few percent of the table, random access through an index costs more than reading the table sequentially. The diagnostic that matters is the gap between estimated and actual rows in EXPLAIN ANALYZE. ## Concurrency vs. Throughput: why more parallelism can make databases slower DevFeed: [Concurrency vs. Throughput: why more parallelism can make databases slower]() Original publisher: [Read original article]() Author: Liz van Dijk Published: 2026-08-07T00:00:00Z Content type: article Language: en Sources: [Blog -- PlanetScale]() Topics: [Databases](), [MySQL](), [vitess](), [Concurrency](), [bug](), [Cloud]() Tags: [bug](), [cloud](), [concurrency](), [databases](), [engineering](), [mysql](), [vitess]() ### AI overview Increasing database parallelism can reduce throughput and destabilize a production system. The article examines how a long-running MySQL transaction, growing version history, retries, and an uncapped request surge caused widespread failures, and explains how Vitess transaction timeouts and connection-pool limits can contain the impact. ### Source excerpt Increasing throughput sometimes requires reducing parallelism. A look into why this is the case for Vitess + MySQL databases ## From Batch Snapshots to Near-Real-Time Data DevFeed: [From Batch Snapshots to Near-Real-Time Data]() Original publisher: [Read original article]() Author: Doximity Published: 2026-08-04T16:29:00Z Content type: article Language: en Sources: [Doximity]() Topics: [data](), [Kafka](), [Streaming](), [MySQL](), [Amazon Aurora]() Tags: [amazon-aurora](), [architecture](), [data](), [kafka](), [mysql](), [pipelines](), [streaming]() ### AI overview Doximity describes combining batch database snapshots with Change Data Capture to make data available in minutes while retaining batch-based consistency and recovery guarantees. The design uses Kafka and includes a trusted snapshot, metadata-preserving routing, a base-plus-delta view, and synthetic cascade deletes. In a 12-day measurement window, 95% of sampled events reached the queryable intermediate layer within eight minutes of publication to Kafka. ### Source excerpt Change Data Capture (CDC) is often presented as a straightforward pipeline: read a database transaction log, publish each change, and apply those changes to another system. That description is accurate, but it leaves out many of the decisions that determine whether the resulting data can be trusted. At Doximity, we already had a batch pipeline that periodically copied snapshots of application databases into our data warehouse. Those snapshots were reliable, but their freshness was measured in hours. We introduced CDC to make changes available in minutes so downstream transformations and operational analytics would not have to wait for the next batch snapshot. We continued using the batch pipeline for the consistency and recovery guarantees it already provided. Over a 12-day measurement window, 95% of events from a stratified sample of active tables reached the queryable intermediate layer within eight minutes of being published to Kafka. The most interesting parts of the project were not the connections from a source database to Kafka or from Kafka to Snowflake, but four questions we had to answer around them: How could we reuse our existing, transactionally consistent batch snapshots as an on-demand starting point for CDC, without reprocessing every existing row? How could we onboard new tables and absorb schema changes from many source databases across our products without growing operational overhead for each one? How could new changes become queryable without waiting for the warehouse to merge them into place? How could we handle cascading child deletes that MySQL performs but never emits as individual binary-log events? Our answers are the four design decisions in this article: a trusted batch snapshot, metadata-preserving routing, a base-plus-delta view, and synthetic cascade deletes. Together, they turned a stream of row changes into a system we could bootstrap, scale, validate, and recover. The sections that follow explain the tradeoffs and guardrails so rea ## Decoding isolation levels: I built a toy DB to force dirty reads and phantom reads DevFeed: [Decoding isolation levels: I built a toy DB to force dirty reads and phantom reads]() Original publisher: [Read original article]() Author: hello@ankit-rana.com Published: 2026-08-02T00:00:00Z Content type: tutorial Language: en Sources: [Ankit Rana | Mechanical Sympathy]() Topics: [Databases](), [PostgreSQL](), [Python](), [MySQL](), [SQL](), [locking]() Tags: [concurrency](), [databases](), [isolation-levels](), [locking](), [mvcc](), [mysql](), [postgres](), [postgresql](), [python](), [sql](), [transactions]() ### AI overview A hands-on tutorial uses a roughly 200-line Python toy database to reproduce transaction anomalies and explain why isolation levels behave differently across PostgreSQL and MySQL InnoDB. It shows that the ANSI SQL isolation table does not fully describe engine behavior, including PostgreSQL's handling of READ UNCOMMITTED and REPEATABLE READ, and MySQL InnoDB's snapshot and next-key locking behavior. ### Source excerpt The ANSI isolation table lists which anomalies each level permits, but it does not describe what your engine actually does: Postgres silently upgrades READ UNCOMMITTED to READ COMMITTED, and its REPEATABLE READ prevents phantoms that the standard allows. Phantom reads are a locking problem rather than a row problem, because you cannot lock a row that does not exist yet. Snapshot isolation stops every anomaly the table names and still permits write skew, which the table never mentions. ## What's new in clickhousectl v0.4.0 DevFeed: [What's new in clickhousectl v0.4.0]() Original publisher: [Read original article]() Author: Al Brown Published: 2026-07-31T11:44:09Z Content type: release Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Command-line interface](), [autoscaling](), [Cloud](), [Kafka](), [MySQL](), [API keys]() Tags: [api-keys](), [autoscaling](), [cli](), [clickhouse](), [cloud](), [cloud-services](), [kafka](), [mysql](), [telemetry]() ### AI overview clickhousectl v0.4.0 introduces horizontal autoscaling for ClickHouse Cloud services, beta ClickPipe schema discovery for Kafka and Kinesis sources, more controls for object storage and MySQL/Postgres ingestion, global OAuth token storage, safer local server lifecycle behavior, and opt-out anonymous usage telemetry. ### Source excerpt clickhousectl v0.4.0 adds horizontal autoscaling for Cloud services, ClickPipe schema discovery, finer control over ClickPipe ingestion, and opt-out anonymous usage telemetry. ## Massively parallel Postgres backups DevFeed: [Massively parallel Postgres backups]() Original publisher: [Read original article]() Author: Ben Dicken Published: 2026-07-31T00:00:00Z Content type: article Language: en Sources: [Blog -- PlanetScale]() Topics: [Databases](), [neki](), [cloud-infrastructure](), [Amazon S3](), [Orchestration](), [Server](), [MySQL](), [Terraform]() Tags: [amazon-s3](), [backup](), [building](), [databases](), [engineering](), [infrastructure](), [mysql](), [neki](), [orchestration](), [postgres](), [scale](), [servers](), [storage]() ### AI overview PlanetScale describes how Neki, its sharded Postgres system, performs consistent encrypted backups at petabyte scale. The approach combines filesystem backups, archived WAL replay, object storage such as Amazon S3, and massive parallelism to back up databases without affecting production queries. ### Source excerpt PlanetScale backs up petabyte-scale sharded Postgres databases in hours using parallel infrastructure, object storage, and WAL replay. ## Everything we announced at Laracon US 2026 DevFeed: [Everything we announced at Laracon US 2026]() Original publisher: [Read original article]() Author: Ana Tavares Published: 2026-07-29T13:40:00Z Content type: article Language: en Sources: [Laravel Blog]() Topics: [Laravel](), [Cloud](), [developer tooling](), [PHP](), [Back end](), [Front end](), [MySQL](), [Next.js](), [Nuxt.js](), [Chrome extension](), [Neovim](), [Sublime Text]() Tags: [announcement](), [backend](), [chrome](), [chrome-extension](), [cloud](), [frontend](), [laravel](), [mysql](), [network](), [next-js](), [php](), [tools](), [vs-code](), [vue]() ### AI overview A roundup of Laracon US 2026 announcements covering Laravel framework updates, Laravel Cloud features, Laravel LSP support for multiple editors, Inertia DevTools, and human-in-the-loop controls for AI agents. ### Source excerpt Every Laravel framework and Cloud announcement from Laracon US 2026, including Laravel LSP, Inertia DevTools, managed queues, and scale-to-zero. ## Session revocations at scale DevFeed: [Session revocations at scale]() Original publisher: [Read original article]() Author: Llew Vallis Published: 2026-07-22T00:00:01Z Content type: article Language: en Sources: [Canva Engineering]() Topics: [sessions](), [Cookies](), [Authorization](), [Caching](), [MySQL](), [scaling](), [gateway](), [Redis](), [reliability]() Tags: [backend](), [caching](), [cookies](), [gateway](), [mysql](), [permissions](), [redis](), [reliability](), [scaling](), [security](), [sessions]() ### AI overview Canva describes how it manages session revocations for hundreds of millions of users. The system keeps revocations in memory for fast gateway checks, while MySQL handles refresh-time lookups; the article explains how loading the cache during deployments created database load and discusses evaluating Redis as a caching solution. ### Source excerpt How Canva keeps hundreds of millions of user sessions fast and secure [Next page]()