Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? How does a data lakehouse work?

Artificial Intelligence 219

Artificial Intelligence Storage Analytics Government 219

The Netflix TechBlog

MARCH 7, 2023

These media focused machine learning algorithms as well as other teams generate a lot of data from the media files, which we described in our previous blog , are stored as annotations in Marken. Similarly, client teams don’t have to worry about when or how the data is written. in a video file.

Media 269

Media Latency Architecture Database 269

Scalegrid

JANUARY 5, 2024

Enhanced data security, better data integrity, and efficient access to information. This article cuts through the complexity to showcase the tangible benefits of DBMS, equipping you with the knowledge to make informed decisions about your data management strategies. What are the key advantages of DBMS?

Efficiency 147

Efficiency Storage Database Scalability 147

VoltDB

MARCH 21, 2024

The law of entropy clearly applies as much to tech stacks and data management as it does to closets and desk drawers. The most obvious and common way this happens is when companies try to evolve their caches into a data platform that can, for example, be used as highly available enterprise key-value stores for volatile data.

Cache 52

Cache Database Storage Availability 52

The Netflix TechBlog

NOVEMBER 12, 2024

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

Latency 224

Latency Cache Infrastructure Strategy 224

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130

Cache Storage Architecture Scalability 130

The Morning Paper

MARCH 8, 2020

Building an elastic query engine on disaggregated storage , Vuppalapati, NSDI’20. This paper describes the design decisions behind the Snowflake cloud-based data warehouse. An increasingly large fraction of data in modern workloads comes from less predictable and highly variable sources. joins) during query processing.

Storage 112

Storage Engineering Cache Serverless 112

The Netflix TechBlog

APRIL 27, 2023

Atlas is an in-memory time-series database that ingests multiple billions of time-series per day and retains the last two weeks of data. To serve the increasing number of push down queries, the in-memory storage layer would need to scale up as well, and it became clear that this would push the already expensive storage costs far higher.

Storage 294

Storage Cache Metrics Database 294

Smashing Magazine

SEPTEMBER 28, 2022

Five Data-Loading Patterns To Improve Frontend Performance. Five Data-Loading Patterns To Improve Frontend Performance. Data loading patterns are an essential part of your application as they will determine which parts of your application are directly usable by visitors. But isn’t waiting for the data the point?

Cache 128

Cache Performance Servers Architecture 128

High Scalability

JANUARY 11, 2022

from a client it performs two parallel operations: i) persisting the action in the data store ii) publish the action in a streaming data store for a pub-sub model. User Feed Service, Media Counter Service) read the actions from the streaming data store and performs their specific tasks. Data Models. Graph Data Models.

Design 334

Design Media Storage Logistics 334

The Netflix TechBlog

SEPTEMBER 24, 2021

As described by the white paper Apple ProRes ( link ), the target data rate of the Apple ProRes HQ for 1920x1080 at 29.97 From chunk encoding to assembly and packaging, the result of each previous processing step must be uploaded to cloud storage and then downloaded by the next processing step. is 220 Mbps.

Cloud 240

Cloud Media Storage Cache 240

ScaleOut Software

APRIL 22, 2020

In this time of extremely high online usage, web sites and services have quickly become overloaded, clogged trying to manage high volumes of fast-changing data. Maintaining rapidly changing data in back-end databases creates bottlenecks that impact responsiveness. The Solution: Distributed Caching.

Cache 52

Cache Storage Servers Database 52

ScaleOut Software

APRIL 22, 2020

In this time of extremely high online usage, web sites and services have quickly become overloaded, clogged trying to manage high volumes of fast-changing data. Maintaining rapidly changing data in back-end databases creates bottlenecks that impact responsiveness. The Solution: Distributed Caching.

Cache 52

Cache Storage Servers Database 52

Percona

FEBRUARY 1, 2023

PostgreSQL is a fantastic database, but if you’re storing images, video, audio files, or other large data objects, you need to “toast” them to get optimal performance. This post will look at using The Oversized-Attribute Storage Technique (TOAST) to improve performance and scalability.

Storage 92

Storage Scalability Strategy Performance 92

Dynatrace

AUGUST 1, 2022

Kubernetes was initially designed with a strong focus on stateless workloads, meaning these workloads do not need to store any persistent data. Interestingly, our partner RedHat reported in 2021 that around 80% of deployed workloads are databases or data caches, storing data in persistent volume claims (PVCs).

Storage 198

Storage Database Network Metrics 198

The Netflix TechBlog

MARCH 10, 2023

are stored in secure storage layers. Amsterdam is built on top of three storage layers. And more specifically, how we index and query over 7TB of data in a read-heavy and continuously growing environment and keep our Elasticsearch cluster healthy. The first layer, Cassandra , is the source of truth for us. Net, Ruby, Perl etc.).

Strategy 262

Strategy Cache Storage Analytics 262

Dynatrace

JANUARY 16, 2023

The study analyzes factual Kubernetes production data from thousands of organizations worldwide that are using the Dynatrace Software Intelligence Platform to keep their Kubernetes clusters secure, healthy, and high performing. Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch.

Open Source 350

Open Source Java Operating System Programming 350

Dynatrace

OCTOBER 7, 2021

This means you no longer have to provision, scale, and maintain servers to run your applications, databases, and storage systems. Speed is next; serverless solutions are quick to spin up or down as needed, and there are no delays due to limited storage or resource access. Data Store. Improving data processing.

Serverless 291

Serverless AWS Lambda Storage 291

Scalegrid

JANUARY 25, 2024

Effective management of memory stores with policies like LRU/LFU proactive monitoring of the replication process and advanced metrics such as cache hit ratio and persistence indicators are crucial for ensuring data integrity and optimizing Redis’s performance. All these contribute significantly towards ensuring smooth functioning.

Metrics 130

Metrics Monitoring Latency Cache 130

The Netflix TechBlog

SEPTEMBER 10, 2024

This allows data to be sent to the device from backend services on demand, without the need for continually polling requests from the device. KeyValue is an abstraction over the storage engine itself, which allows us to choose the best storage engine that meets our SLO needs.

Latency 228

Latency Cache Tuning Efficiency 228

The Netflix TechBlog

MARCH 8, 2021

Historically artists had these machines built for them at their desks and only had access to the data and applications when they were in the office. They could need a GPU when doing graphics-intensive work or extra large storage to handle file management. Artists need many components to be customized.

Entertainment 307

Entertainment Storage Hardware Open Source 307

Percona

APRIL 24, 2023

The more indexes, the more the requirement of memory for effective caching. Indexes need more cache than tables Due to random writes and reads, indexes need more pages to be in the cache. Cache requirements for indexes are generally much higher than associated tables.

Tuning 128

Tuning Cache Storage Database 128

Percona

FEBRUARY 15, 2023

With MyRocks/RocksDB, data is stored in a set of large SST files. For good performance, the filter blocks are cached in the RocksDB block cache and normally stay there since they are accessed frequently. LSM storage engines like MyRocks are very different from the more common B-Tree-based storage engines like InnoDB.

Storage 129

Storage Tuning Cache Engineering 129

Scalegrid

DECEMBER 21, 2023

In today’s data-driven world, the ability to effectively monitor and manage data is of paramount importance. Redis®, a powerful in-memory data store, is no exception. To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold.

Strategy 130

Strategy Monitoring Latency DevOps 130

Dynatrace

DECEMBER 13, 2023

This includes how quickly the application loads, how much load it is putting on the device, how much storage is being used, and how frequently it crashes. Here are some ways observability data is important to mobile app performance monitoring. Issue remediation. Proactive monitoring. Performance optimization.

Best Practices 209

Best Practices Mobile Metrics Performance 209

n0derunner

JULY 23, 2019

Effect of removing CPU constraints and maintaining data locality on a running DB instance. As the DB continues to run on the new host – the Nutanix storage detects the access patterns and “localizes” the data that the DB is accessing. The post Impact of Data locality on DB workloads.

Benchmarking 76

Benchmarking Storage Cache Tuning 76

The Morning Paper

NOVEMBER 5, 2019

File systems unfit as distributed storage backends: lessons from 10 years of Ceph evolution Aghayev et al., In this case, the assumption that a distributed storage backend should clearly be layered on top of a local file system. What is a distributed storage backend? SOSP’19. This is not surprising in hindsight.

Storage 64

Storage Systems Hardware Efficiency 64

The Morning Paper

SEPTEMBER 10, 2019

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., Anchored in the primary use case of supporting Google’s YouTube business, what we’re looking at here could well be the future of data processing at Google. Because they had too many data processing systems! ;). VLDB’19. are divided.

Analytics 75

Analytics Latency Cache Google 75

Percona

APRIL 17, 2023

We’ll also go over some best practices for MongoDB security as well as MongoDB data modeling. You can set this by adding the following lines to the /etc/sysctl.conf : vm.dirty_ratio = 15 vm.dirty_background_ratio = 5 Filesystems mount options MongoDB recommends the XFS filesystem for on-disk database data.

Best Practices 52

Best Practices Design Tuning Database 52

Percona

MARCH 28, 2023

It’s to ensure that our data is durable after each write operation and to make it persistent and consistent without compromising the performance. In terms of MongoDB, it achieves WAL and data durability using a combination of both Journaling and Checkpoints. Starting with the basics, why is WAL needed in the first place?

Hardware 89

Hardware C++ Storage Cache 89

Percona

APRIL 7, 2023

I’ve used a fourth instance to host a PMM server to monitor servers A and B and used the data collected by the PMM agents installed on the database servers to compare performance. In MySQL, considering the standard storage engine, InnoDB , the data cache is called Buffer Pool.

Tuning 138

Tuning Cache Servers Benchmarking 138

Percona

MARCH 23, 2023

By caching hot datasets, indexes, and ongoing changes, InnoDB can provide faster response times and utilize disk IO in a much more optimal way. Storage The type of storage and disk used for database servers can have a significant impact on performance and reliability. Setting oom_score_adj to -800.

Performance 128

Performance Hardware Tuning Storage 128

Percona

DECEMBER 23, 2022

I wrote this post on MyRocks because I believe it is the most interesting new MySQL storage engine to have appeared over the last few years. I decided to use a virtual machine with two CPU cores, four GB of memory, and storage limited to a maximum of 1000 IOPs of 16KB. I emulated these limits using the KVM iotune settings in my lab. <iotune>

Storage 55

Storage Cache C++ Virtualization 55

Dynatrace

DECEMBER 20, 2021

Replay tools log data from users’ interactions with your website or application, including the pages they looked at, how long they stayed, and what they clicked on while they were there. These tools pull this data to recreate anonymized versions of user sessions that your team can watch back on demand. Improved analytic context.

Mobile 254

Mobile Website Analytics Cache 254

Percona

JULY 25, 2023

When a new node joins the cluster, SST is performed to receive the data from DONOR to the JOINER. JOINER uses PXB to stream the data directory from DONOR. Percona XtraBackup copies the InnoDB data files. Percona XtraBackup copies the InnoDB data files. ibd2sdi data/test/t1.ibd ibd2sdi data/test/t1.ibd

Cache 88

Cache Servers Benchmarking Design 88

Scalegrid

JUNE 14, 2024

In today’s data-driven world, organizations rely heavily on data analysis and visualization to make informed decisions and gain a competitive edge. It provides a user-friendly interface and a wide range of tools to transform raw data into meaningful insights. Why connect Power BI to a MySQL Database?

Database 130

Database Azure Efficiency Servers 130