DZone

SEPTEMBER 3, 2024

However, the increasing sizes of both data volumes and distributed system clusters raise significant cost challenges for all-flash storage and vast operational challenges for kernel clients. It improves I/O throughput substantially through the distributed cache and uses cost-effective object storage for data storage.

Cache 147

Cache Performance Storage Architecture 147

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

Percona

APRIL 14, 2023

A shared characteristic in most (if not all) databases, be them traditional relational databases like Oracle, MySQL, and PostgreSQL or some kind of NoSQL-style database like MongoDB, is the use of a caching mechanism to keep (a copy of) part of the data in memory. So, how do you know if your hot data is in memory? MySQL does.

Cache 107

Cache Efficiency Database Monitoring 107

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 297

Storage Cache Metrics Database 297

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 325

Serverless AWS Lambda Storage 325

Scalegrid

MAY 11, 2024

MongoDB offers several storage engines that cater to various use cases. The default storage engine in earlier versions was MMAPv1, which utilized memory-mapped files and document-level locking. The newer, pluggable storage engine, WiredTiger, addresses this by using prefix compression, collection-level locking, and row-based storage.

Storage 130

Storage Engineering Cache Database 130

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 242

Cloud Media Storage Cache 242

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 358

Open Source Java Operating System Programming 358

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 246

Storage Database Network Metrics 246

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 Open Source Hardware 307

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

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

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 141

Cache Performance Servers Architecture 141

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 264

Strategy Cache Storage Analytics 264

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

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 264

Mobile Website Analytics Cache 264

Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154

Big Data Processing Lambda Database 154

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 111

Storage Scalability Strategy Performance 111

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 246

Best Practices Mobile Metrics Performance 246

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 234

Latency Cache Tuning Efficiency 234

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 Netflix TechBlog

MAY 4, 2023

It can happen on an edge API system servicing customer devices, between the edge and mid-tier services, or from mid-tiers to data stores. Given the scale of the data being generated using replay traffic, we record the responses from the two sides to a cost-effective cold storage facility using technology like Apache Iceberg.

Traffic 347

Traffic Latency Tuning Systems 347

Dynatrace

SEPTEMBER 13, 2023

These workflows also utilize Davis® , the Dynatrace causal AI engine, and all your observability and security data across all platforms, in context, at scale, and in real-time. Storing frequently accessed data in faster storage, usually in-memory caching, improves data retrieval speed and overall system performance. Beyond

AWS 305

AWS Efficiency Azure Cloud 305

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 139

Tuning Cache Storage Database 139

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 138

Storage Tuning Cache Engineering 138

All Things Distributed

OCTOBER 12, 2016

Fast Data is an emerging industry term for information that is arriving at high volume and incredible rates, faster than traditional databases can manage. Three years ago, as part of our AWS Fast Data journey we introduced Amazon ElastiCache for Redis , a fully managed in-memory data store that operates at sub-millisecond latency.

Scalability 100

Scalability Cache Analytics AWS 100

Dynatrace

OCTOBER 15, 2021

Let’s take a closer look and clear up any confusion about what it is, the telemetry data it covers, and the benefits it can provide. Loosely defined, observability is the ability to understand what’s happening inside a system from the knowledge of the external data it produces, which are usually logs, metrics, and traces.

Open Source 246

Open Source Metrics Cloud Transportation 246

All Things Distributed

SEPTEMBER 20, 2013

Traditionally records in a database were stored as such: the data in a row was stored together for easy and fast retrieval. Combined with the rise of data warehouse workloads, where there is often significant redundancy in the values stored in columns, and database models based on column oriented storage took off.

Storage 71

Storage Hardware Cache C++ 71

Dynatrace

NOVEMBER 5, 2019

With an all-in-one, fully automated, platform Dynatrace brings some unique values to the table for applications deployed on Microsoft Azure including: Dynatrace OneAgent – The Dynatrace OneAgent allows for an automatic approach to collecting monitoring data and business. Hybrid and multi-cloud platform –. Migrating to the cloud.

Azure 198

Azure Artificial Intelligence Metrics Innovation 198

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 144

Performance Hardware Tuning Storage 144

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

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 145

Tuning Cache Servers Benchmarking 145

Dynatrace

SEPTEMBER 17, 2019

Some vendors have just bolted on individual capabilities which often leads to six data silos. PostgreSQL & Elastic for data storage. REDIS for caching. MaaSS for Business: Data per SaaS-Tenant. The Business teams therefore built a set of dashboards that contain the data they want to see.

AWS 170

AWS Monitoring Ecommerce Lambda 170

All Things Distributed

AUGUST 22, 2011

Today AWS has launched Amazon ElastiCache , a new service that makes it easy to add distributed in-memory caching to any application. Amazon ElastiCache handles the complexity of creating, scaling and managing an in-memory cache to free up brainpower for more differentiating activities. Driving Storage Costs Down for AWS Customers.

Cloud 103

Cloud Cache AWS Storage 103

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

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