Empowering Data Intelligence with Distributed SQL for Sharding, Scalability, and Security Across All Databases.
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Découvrez des skills réutilisables pour les AI agents.
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Résultats de recherche: sharding
Annuaire en anglaisA curated set of agent skills for Qdrant vector search, providing structured knowledge on scaling, optimization, monitoring, deployment, and SDK usage.
MySQL Proxy using Java NIO based on Sharding SQL,Calcite ,simple and fast
SPD V1 Batch. Process large, user-supplied sets of legitimate product, software, startup, app, and AI-tool directory URLs across Windows, macOS, and Linux-capable environments through normalization, deduplication, execution sharding, verification-first queues, authorization-controlled form work, idempotent submission, recovery, and truthful throughput reporting. Use when coverage and operational throughput matter more than deep per-site quality analysis. Do not use for ranking manipulation, bulk link spam, invented data, CAPTCHA bypass, paid-link acquisition, forced reciprocal links, or routes prohibited by a site's terms.
Use this skill for Pest PHP testing in Laravel projects only. Trigger whenever any test is being written, edited, fixed, or refactored — including fixing tests that broke after a code change, adding assertions, converting PHPUnit to Pest, adding datasets, and TDD workflows. Always activate when the user asks how to write something in Pest, mentions test files or directories (tests/Feature, tests/Unit, tests/Browser), or needs browser testing, smoke testing multiple pages for JS errors, or architecture tests. Covers: test()/it()/expect() syntax, datasets, mocking, browser testing (visit/click/fill), smoke testing, arch(), Livewire component tests, RefreshDatabase, and all Pest 4 features. Do not use for factories, seeders, migrations, controllers, models, or non-test PHP code.
A sharding proxy for MYSQL databases
KunlunBase is a distributed relational database management system(RDBMS) with complete NewSQL capabilities and robust transaction ACID guarantees and is compatible with standard SQL. Applications which used PostgreSQL or MySQL can work with KunlunBase as-is without any code change or rebuild because KunlunBase supports both PostgreSQL and MySQL connection protocols and DML SQL grammars. MySQL DBAs can quickly work on a KunlunBase cluster because we use MySQL as storage nodes of KunlunBase. KunlunBase can elastically scale out as needed, and guarantees transaction ACID under error conditions, and KunlunBase fully passes TPC-C, TPC-H and TPC-DS test suites, so it not only support OLTP workloads but also OLAP workloads. Application developers can use KunlunBase to build IT systems that handles terabytes of data, without any effort on their part to implement data sharding, distributed transaction processing, distributed query processing, crash safety, high availability, strong consistency, horizontal scalability. All these powerful features are provided by KunlunBase. KunlunBase supports powerful and user friendly cluster management, monitor and provision features, can be readily used as DBaaS.