企业版MySQL数据库_MySQL
MySQL是开源方面的领军企业，同时也是全球成长最快的开源数据库开发商之一。作为全球最流行的开源数据库软件，MySQL企业版是公司的旗舰产品，包括经过产品测试的软件、主动监测工具和金牌支持服务。
许多全球最大、增长最快的企业和机构，包括行业领导者如雅虎、阿尔卡特-朗讯、谷歌、诺基亚、YouTube和Booking.com均采用MySQL产品，省时、省钱地创建大量网站、关键业务系统和打包软件。MySQL的开源数据库广泛部署于所有主要的操作系统，硬件用户、所涉地区、应用行业、应用类型极其广泛。MySQL的高性能开源数据库软件已经被下载和发行超过1亿套，并且正以每天下载5万套的数量增长。
MySQL开源数据库是LAMP架构(由Linux、Apache、MySQL和PHP/Perl组成的、通常被看作是互联网基础)中的“M”。来自MySQL的数据库，还有OpenSolaris和GlassFish，加上Sun的Java平台和NetBeans社区，将为转移应用到Web的广大客户开创一个强大的Web应用平台。
MySQL Enterprise Server软件是最可靠、最安全、更新版本的MySQL企业级服务器数据库，它能够高性价比地提供电子商务、联机事务处理(OLTP)、千兆规模的数据仓库应用等。它是一个安全的事务处理、适应ACID的数据库，能提供完整的提交、反转、崩溃恢复和行级锁定功能。MySQL数据库因其易用性、可扩展性和高性能等特点，成为全球最流行的开源数据库。
MySQL Enterprise Server 5.0提供了新的企业级产品功能，其中包括：
ACID事务处理：用以建立可靠安全的关键应用
存储过程：可以提高开发人员的工作效率
触发器：使用户能在数据库层面完成复杂的商业逻辑
视图： 确保敏感数据不被窃取
信息计划：为查询元数据提供快速的途径
分布式处理：通过它可以支持跨多个数据库的复杂事务处理
可插拔存储引擎架构：为数据库设计实施提供极大的灵活性
Archive存储引擎：提供了历史数据和审计数据的管理平台
Federated存储引擎：可以将多个不同服务器上的数据建立到一个统一的逻辑数据库
MySQL还提供了全套数据库驱动和绘图工具，用以帮助开发者和数据库管理员建立和管理其MySQL应用，如下：
(1)MySQL驱动
MySQL Native C Library
MySQL Drivers for ODBC, JDBC, .NET
Community Drivers for PHP, Perl, Python, Ruby, etc
MySQL Connector/MXJ for deployment as a JMX MBean
(2)MySQL图形工具
MySQL Workbench
MySQL Query Browser
MySQL Administrator
MySQL Migration Toolkit
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15 recommended open source free image annotation tools
Mar 28, 2024 pm 01:21 PM
Image annotation is the process of associating labels or descriptive information with images to give deeper meaning and explanation to the image content. This process is critical to machine learning, which helps train vision models to more accurately identify individual elements in images. By adding annotations to images, the computer can understand the semantics and context behind the images, thereby improving the ability to understand and analyze the image content. Image annotation has a wide range of applications, covering many fields, such as computer vision, natural language processing, and graph vision models. It has a wide range of applications, such as assisting vehicles in identifying obstacles on the road, and helping in the detection and diagnosis of diseases through medical image recognition. . This article mainly recommends some better open source and free image annotation tools. 1.Makesens
Ten recommended open source free text annotation tools
Mar 26, 2024 pm 08:20 PM
Text annotation is the work of corresponding labels or tags to specific content in text. Its main purpose is to provide additional information to the text for deeper analysis and processing, especially in the field of artificial intelligence. Text annotation is crucial for supervised machine learning tasks in artificial intelligence applications. It is used to train AI models to help more accurately understand natural language text information and improve the performance of tasks such as text classification, sentiment analysis, and language translation. Through text annotation, we can teach AI models to recognize entities in text, understand context, and make accurate predictions when new similar data appears. This article mainly recommends some better open source text annotation tools. 1.LabelStudiohttps://github.com/Hu
Recommended: Excellent JS open source face detection and recognition project
Apr 03, 2024 am 11:55 AM
Face detection and recognition technology is already a relatively mature and widely used technology. Currently, the most widely used Internet application language is JS. Implementing face detection and recognition on the Web front-end has advantages and disadvantages compared to back-end face recognition. Advantages include reducing network interaction and real-time recognition, which greatly shortens user waiting time and improves user experience; disadvantages include: being limited by model size, the accuracy is also limited. How to use js to implement face detection on the web? In order to implement face recognition on the Web, you need to be familiar with related programming languages and technologies, such as JavaScript, HTML, CSS, WebRTC, etc. At the same time, you also need to master relevant computer vision and artificial intelligence technologies. It is worth noting that due to the design of the Web side
Alibaba 7B multi-modal document understanding large model wins new SOTA
Apr 02, 2024 am 11:31 AM
New SOTA for multimodal document understanding capabilities! Alibaba's mPLUG team released the latest open source work mPLUG-DocOwl1.5, which proposed a series of solutions to address the four major challenges of high-resolution image text recognition, general document structure understanding, instruction following, and introduction of external knowledge. Without further ado, let’s look at the effects first. One-click recognition and conversion of charts with complex structures into Markdown format: Charts of different styles are available: More detailed text recognition and positioning can also be easily handled: Detailed explanations of document understanding can also be given: You know, "Document Understanding" is currently An important scenario for the implementation of large language models. There are many products on the market to assist document reading. Some of them mainly use OCR systems for text recognition and cooperate with LLM for text processing.
Just released! An open source model for generating anime-style images with one click
Apr 08, 2024 pm 06:01 PM
Let me introduce to you the latest AIGC open source project-AnimagineXL3.1. This project is the latest iteration of the anime-themed text-to-image model, aiming to provide users with a more optimized and powerful anime image generation experience. In AnimagineXL3.1, the development team focused on optimizing several key aspects to ensure that the model reaches new heights in performance and functionality. First, they expanded the training data to include not only game character data from previous versions, but also data from many other well-known anime series into the training set. This move enriches the model's knowledge base, allowing it to more fully understand various anime styles and characters. AnimagineXL3.1 introduces a new set of special tags and aesthetics
Single card running Llama 70B is faster than dual card, Microsoft forced FP6 into A100 | Open source
Apr 29, 2024 pm 04:55 PM
FP8 and lower floating point quantification precision are no longer the "patent" of H100! Lao Huang wanted everyone to use INT8/INT4, and the Microsoft DeepSpeed team started running FP6 on A100 without official support from NVIDIA. Test results show that the new method TC-FPx's FP6 quantization on A100 is close to or occasionally faster than INT4, and has higher accuracy than the latter. On top of this, there is also end-to-end large model support, which has been open sourced and integrated into deep learning inference frameworks such as DeepSpeed. This result also has an immediate effect on accelerating large models - under this framework, using a single card to run Llama, the throughput is 2.65 times higher than that of dual cards. one
1.3ms takes 1.3ms! Tsinghua's latest open source mobile neural network architecture RepViT
Mar 11, 2024 pm 12:07 PM
Paper address: https://arxiv.org/abs/2307.09283 Code address: https://github.com/THU-MIG/RepViTRepViT performs well in the mobile ViT architecture and shows significant advantages. Next, we explore the contributions of this study. It is mentioned in the article that lightweight ViTs generally perform better than lightweight CNNs on visual tasks, mainly due to their multi-head self-attention module (MSHA) that allows the model to learn global representations. However, the architectural differences between lightweight ViTs and lightweight CNNs have not been fully studied. In this study, the authors integrated lightweight ViTs into the effective
Domestic open source MoE indicators explode: GPT-4 level capabilities, API price is only one percent
May 07, 2024 pm 05:34 PM
The latest large-scale domestic open source MoE model has become popular just after its debut. The performance of DeepSeek-V2 reaches GPT-4 level, but it is open source, free for commercial use, and the API price is only one percent of GPT-4-Turbo. Therefore, as soon as it was released, it immediately triggered a lot of discussion. Judging from the published performance indicators, DeepSeekV2's comprehensive Chinese capabilities surpass those of many open source models. At the same time, closed source models such as GPT-4Turbo and Wenkuai 4.0 are also in the first echelon. The comprehensive English ability is also in the same first echelon as LLaMA3-70B, and surpasses Mixtral8x22B, which is also a MoE. It also shows good performance in knowledge, mathematics, reasoning, programming, etc. And supports 128K context. Picture this
