Background: If you did not read my first blog post about why I am sharing my thoughts on the benchmarks published by Mark Callaghan on Small Datum you may want to skim through it now for a little context:“Thoughts on Small Datum – Part 1”
~~~~~~~~~~~~~~~~~~~~~~~~
Last time, in“Thoughts on Small Datum – Part 2”I shared my cliff notes and a graph onMark Callaghan’s (@markcallaghan) March 11th insertion rate benchmarks using flash storage media. In those tests he comparesMySQL outfitted with theInnoDBstorage engine against two distributions ofMongoDB: basic MongoDB fromMongoDB, Inc.andTokuMX(the high-performance distribution of MongoDB from Tokutek).
Later, in his March 24th“TokuMX, MongoDB and InnoDB Versus the Insert Benchmark with Disks”Mark presents similar benchmark findings for a new set of insertion rate tests using a different benchmark and the same DBMS products. This time however he uses servers configured with traditional disk storage media instead of flash. In addition he does a number of things to configure the products and tests differently than he did in the flash storage benchmarks.
As the saying goes, a picture is worth a thousand words. The X-axis here is the number of rows being inserted at each stage of the test. The Y-axis is the insertion rate recorded at those levels (and in this case,biggeris better).
As you can see, Mark found that TokuMX outperforms MySQL/InnoDB as well as basic MongoDB. He also found that shortly after 500M rows it became impractical to test MongoDB (it was taking unreasonably long time to let the test run to completion). The same thing happened with MySQL/InnoDB after 1.6B rows. TokuMX was still running strong at 2B rows.
Note: Mark tests several different configurations of MongoDB, trying to find the optimum configuration. For the purposes of my visual aid I selected the fastest / best MongoDB configuration at each level of 100M rows. That’s not very scientific of me but I wanted to be as fair as possible in the visual comparison.
Bottom Line:Like the flash storage test covered last time, the tests with traditional disk storage show that both MySQL with InnoDB and TokuMX significantly outperform basic MongoDB in benchmarks testing for write-intensive applications. Both MongoDB (540M rows) and MySQL/InnoDB (1.6B rows) become unresponsive in these tests as the database gets large.
This suggests that if your application is a write-intensive NoSQL one, and your servers are outfitted with traditional disk storage, it will perform significantly better on the TokuMX high-performance distribution of MongoDB. And that, with TokuMX performance will not degrade significantly as the database grows. It also shows basic MongoDB may not even be suitable for write-intensive applications that are expected to grow beyond 500M rows.
One footnote: TokuDB (the Tokutek high-performance MySQL storage engine alternative to InnoDB that employees the same underlying technology as TokuMX) isnotcovered in Mark’s benchmark. That’s too bad because it delivers better performance and scalability than InnoDB for your NewSQL applications.
You can read all the gory details on Mark’sMarch 24th insertion rate benchmark here. And, you can download and tryTokuMX for yourself (for free) here.
As always, your thoughts and comments are welcome below. You can also reach me on Twitter via@dcrosenlund.
Next time, in Thoughts on Small Datum – Part 4, this marketer’s summary and graphs for Mark’sIO-bound point queries tests using sysbench.

MySQL和SQLite的主要区别在于设计理念和使用场景:1.MySQL适用于大型应用和企业级解决方案,支持高性能和高并发;2.SQLite适合移动应用和桌面软件,轻量级且易于嵌入。

MySQL中的索引是数据库表中一列或多列的有序结构,用于加速数据检索。1)索引通过减少扫描数据量提升查询速度。2)B-Tree索引利用平衡树结构,适合范围查询和排序。3)创建索引使用CREATEINDEX语句,如CREATEINDEXidx_customer_idONorders(customer_id)。4)复合索引可优化多列查询,如CREATEINDEXidx_customer_orderONorders(customer_id,order_date)。5)使用EXPLAIN分析查询计划,避

在MySQL中使用事务可以确保数据一致性。1)通过STARTTRANSACTION开始事务,执行SQL操作后用COMMIT提交或ROLLBACK回滚。2)使用SAVEPOINT可以设置保存点,允许部分回滚。3)性能优化建议包括缩短事务时间、避免大规模查询和合理使用隔离级别。

选择PostgreSQL而非MySQL的场景包括:1)需要复杂查询和高级SQL功能,2)要求严格的数据完整性和ACID遵从性,3)需要高级空间功能,4)处理大数据集时需要高性能。PostgreSQL在这些方面表现出色,适合需要复杂数据处理和高数据完整性的项目。

MySQL数据库的安全可以通过以下措施实现:1.用户权限管理:通过CREATEUSER和GRANT命令严格控制访问权限。2.加密传输:配置SSL/TLS确保数据传输安全。3.数据库备份和恢复:使用mysqldump或mysqlpump定期备份数据。4.高级安全策略:使用防火墙限制访问,并启用审计日志记录操作。5.性能优化与最佳实践:通过索引和查询优化以及定期维护兼顾安全和性能。

如何有效监控MySQL性能?使用mysqladmin、SHOWGLOBALSTATUS、PerconaMonitoringandManagement(PMM)和MySQLEnterpriseMonitor等工具。1.使用mysqladmin查看连接数。2.用SHOWGLOBALSTATUS查看查询数。3.PMM提供详细性能数据和图形化界面。4.MySQLEnterpriseMonitor提供丰富的监控功能和报警机制。

MySQL和SQLServer的区别在于:1)MySQL是开源的,适用于Web和嵌入式系统,2)SQLServer是微软的商业产品,适用于企业级应用。两者在存储引擎、性能优化和应用场景上有显着差异,选择时需考虑项目规模和未来扩展性。

在需要高可用性、高级安全性和良好集成性的企业级应用场景下,应选择SQLServer而不是MySQL。1)SQLServer提供企业级功能,如高可用性和高级安全性。2)它与微软生态系统如VisualStudio和PowerBI紧密集成。3)SQLServer在性能优化方面表现出色,支持内存优化表和列存储索引。


热AI工具

Undresser.AI Undress
人工智能驱动的应用程序,用于创建逼真的裸体照片

AI Clothes Remover
用于从照片中去除衣服的在线人工智能工具。

Undress AI Tool
免费脱衣服图片

Clothoff.io
AI脱衣机

Video Face Swap
使用我们完全免费的人工智能换脸工具轻松在任何视频中换脸!

热门文章

热工具

SublimeText3 英文版
推荐:为Win版本,支持代码提示!

记事本++7.3.1
好用且免费的代码编辑器

SublimeText3汉化版
中文版,非常好用

mPDF
mPDF是一个PHP库,可以从UTF-8编码的HTML生成PDF文件。原作者Ian Back编写mPDF以从他的网站上“即时”输出PDF文件,并处理不同的语言。与原始脚本如HTML2FPDF相比,它的速度较慢,并且在使用Unicode字体时生成的文件较大,但支持CSS样式等,并进行了大量增强。支持几乎所有语言,包括RTL(阿拉伯语和希伯来语)和CJK(中日韩)。支持嵌套的块级元素(如P、DIV),

禅工作室 13.0.1
功能强大的PHP集成开发环境