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HammerDB for Managers

HammerDB

The wide range of database support gives HammerDB an advantage over other database benchmarking tools that only implement workloads against one or two databases, limiting comparison between database engines and assessing relative performance. When reporting TPROC-C workloads the key metric is known as NOPM or New Orders per Minute.

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MariaDB vs MySQL: Key Differences and Use Cases

Percona

In this blog, we’ll provide a comparison between MariaDB vs. MySQL (including Percona Server for MySQL ). MariaDB retains compatibility with MySQL, offers support for different programming languages, including Python, PHP, Java, and Perl, and works with all major open source storage engines such as MyRocks, Aria, and InnoDB.

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Choosing a cloud DBMS: architectures and tradeoffs

The Morning Paper

We group the DBMS design choices and tradeoffs into three broad categories, which result from the need for dealing with (A) external storage; (B) query executors that are spun on demand; and (C) DBMS-as-a-service offerings. Query performance is measured from both warm and cold caches. Key findings. Serverless o?erings

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SQL Server on IoT Edge and Developer Machines – Smaller Footprint

SQL Server According to Bob

For example, Azure SQL Database Edge can already use TSQL Predict Machine Learning (ML) and Column Storage. The lock manager has partitions, lock block cache and other structures. Reduce the number of partitions and size of the cache. IO Request Caches. SQLPAL may cache I/O request structures with each thread.

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Using Parallel Query with Amazon Aurora for MySQL

Percona

now has a version which will support parallelism for SELECT queries (utilizing the read capacity of storage nodes underneath the Aurora cluster). Aurora Parallel Query response time (for queries which can not use indexes) can be 5x-10x better compared to the non-parallel fully cached operations. Aurora instance type and comparison.

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A persistent problem: managing pointers in NVM

The Morning Paper

The beauty of persistent memory is that we can use memory layouts for persistent data (with some considerations for volatile caches etc. The Twizzler KVS (key-value store) is just 250 lines of C code, and uses one persistent object for the index structure, and a second one for the data. in front of that memory , as we saw last week).

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MongoDB Database Backup: Best Practices & Expert Tips

Percona

Cons of logical backups As it reads all data, it can be slow and will require disk reads too for databases that are larger than the RAM available for the WT cache—the WT cache pressure increases, which slows down the performance. Especially if going into or out of storage types that may throttle bandwidth/network traffic.