Dynatrace

JANUARY 31, 2024

million” – Gartner Data observability is a practice that helps organizations understand the full lifecycle of data, from ingestion to storage and usage, to ensure data health and reliability. . “Every year, poor data quality costs organizations an average $12.9

DevOps 192

DevOps Analytics Airlines Metrics 192

Highly Scalable

SEPTEMBER 18, 2012

Historically, NoSQL paid a lot of attention to tradeoffs between consistency, fault-tolerance and performance to serve geographically distributed systems, low-latency or highly available applications. Read/Write latency. Read/Write requests are processes with a minimal latency. Data Placement. Read/Write scalability.

Database 213

Database Latency C++ Scalability 213

The Morning Paper

AUGUST 29, 2019

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. Another interesting experiment here compared the effects on performance of different storage types.

Architecture 76

Architecture Cloud Storage Serverless 76

The Morning Paper

DECEMBER 8, 2019

Therefore any programming abstraction must be low latency and the kernel needs to be kept off the path of persistent data access as much as possible. 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.

Hardware 56

Hardware Programming Media Storage 56

Percona

MAY 2, 2023

The speed of backup also depends on allocated IOPS and type of storage since lots of read/writes would be happening during this process. Back up anywhere – to the cloud (use any S3-compatible storage) or on-premise with a locally-mounted remote file system It allows you to choose which compression algorithms to use.

Best Practices 52

Best Practices Database Storage Servers 52

HammerDB

OCTOBER 12, 2018

This post complements the previous best practice guides this time with the focus on MySQL and MariaDB and achieving top levels of performance with the HammerDB MySQL TPC-C test. As is also the case this limitation is at the database level (especially the storage engine) rather than the hardware level. order by c.

Best Practices 40

Best Practices Scalability Performance C++ 40

Highly Scalable

MAY 1, 2012

This approach often leads to heavyweight high-latency analytical processes and poor applicability to realtime use cases. The straightforward approaches for implementation of this system are: Log all events in a large storage like Hadoop and compute unique visitor periodically using heavy MapReduce jobs or whatever.

Analytics 191

Analytics Traffic Big Data Efficiency 191