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. This article will explore how they handle data storage and scalability, perform in different scenarios, and, most importantly, how these factors influence your choice.

Cache 130

Cache Storage Scalability Architecture 130

Dynatrace

JUNE 8, 2021

Continuous improvement of services is the most efficient process for all teams that are looking to improve the performance of their applications by considering all layers of their architecture. Similar to an athlete, the objective here is to have teams always push the limits to become faster and stronger.

Metrics 166

Metrics Tuning Programming Systems 166

ACM Sigarch

OCTOBER 4, 2018

On the other hand, one can implement this system with encryption/decryption units between the compute and the storage. This allows the same database to be implemented while removing storage and connections from the trust boundary. These two techniques serve complementary purposes: Probabilistic encryption hides data stored at rest.

Systems 47

Systems Hardware Storage Healthcare 47

The Morning Paper

JUNE 16, 2019

The challenging thing of course, is efficiently maintaining all of these parallel universes. If we do that naively though, we’re going to end up with a lot of universes to store and maintain and the storage requirements alone will be prohibitive. These ideas make an efficient multiverse database possible.

Database 90

Database Cache Benchmarking Efficiency 90

All Things Distributed

AUGUST 16, 2012

An apples to apples comparison of the costs associated with running various usage patterns on-premises and with AWS requires more than a simple comparison of hardware expense versus always-on utility pricing for compute and storage. Massive economies of scale and efficiency improvements allow AWS to continually lower prices.

AWS 118

AWS Hardware Traffic Best Practices 118

The Morning Paper

JANUARY 30, 2020

For comparison, the server bar also shows performance when the full application runs on the server. Future work includes delving into more realistic use cases and addressing other challenges related to mobile computing such as energy efficiency. In the physics app edge processing yields 1.6x for the wasm-version.

Mobile 104

Mobile Cloud Latency Games 104

Scalegrid

JULY 17, 2020

JSONB supports indexing the JSON data, and is very efficient at parsing and querying the JSON data. JSONB storage has some drawbacks vs. traditional columns: PostreSQL does not store column statistics for JSONB columns. JSONB storage results in a larger storage footprint. It is a decomposed binary format to store JSON.

Storage 321

Storage Database Efficiency Processing 321

Scalegrid

JANUARY 8, 2024

Real-world examples like Spotify’s multi-cloud strategy for cost reduction and performance, and Netflix’s hybrid cloud setup for efficient content streaming and creation, illustrate the practical applications of each model. Thus making it an ideal choice for businesses seeking a successful implementation of their multi-cloud strategy.

Strategy 147

Strategy Cloud Scalability Artificial Intelligence 147

The Netflix TechBlog

JUNE 13, 2023

We can start by dialing traffic in a single data center to allow for an easier side-by-side comparison of key metrics across data centers, thereby making it easier to observe any deviations in the metrics. One can perform this comparison live on the request path or offline based on the latency requirements of the particular use case.

Traffic 279

Traffic Metrics Systems Strategy 279

Percona

DECEMBER 11, 2023

A Dedicated Log Volume (DLV) is a specialized storage volume designed to house database transaction logs separately from the volume containing the database tables. This separation aims to streamline transaction write logging, improving efficiency and consistency. Who can benefit from DLV? and later v10 versions MySQL: 8.0.28

AWS 93

AWS Benchmarking Performance Traffic 93

Percona

SEPTEMBER 1, 2023

Character encoding refers to the method used to represent characters as binary data for storage and transmission. The choice of character set and encoding impacts not only efficiency but also how the data appears to users. This difference in storage size can lead to variations in the size of index entries, which can impact efficiency.

Performance 52

Performance Storage Social Media Database 52

SQL Performance

APRIL 5, 2019

The more violations, the worse the clustered unique index performs by comparison. For a clustered unique index with IGNORE_DUP_KEY set, duplicates are handled by the storage engine. The query processor removes duplicates from the insert stream, ensuring that no duplicates are seen by the storage engine. The trade-off.

Storage 53

Storage Servers Engineering Testing 53

The Netflix TechBlog

SEPTEMBER 24, 2021

Figure 1: A Simplified Video Processing Pipeline With this architecture, chunk encoding is very efficient and processed in distributed cloud computing instances. 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.

Cloud 237

Cloud Media Storage Cache 237

Percona

MARCH 29, 2023

Compression in any database is necessary as it has many advantages, like storage reduction, data transmission time, etc. Storage reduction alone results in significant cost savings, and we can save more data in the same space. By default, MongoDB provides a snappy block compression method for storage and network communication.

Storage 105

Storage Network Open Source Latency 105

The Netflix TechBlog

FEBRUARY 13, 2023

We have been leveraging machine learning (ML) models to personalize artwork and to help our creatives create promotional content efficiently. Media Feature Storage: Amber Storage Media feature computation tends to be expensive and time-consuming. We accomplish this by paving the path to: Accessing and processing media data (e.g.

Media 290

Media Storage Infrastructure Systems 290

Dynatrace

NOVEMBER 4, 2022

Overall, 53% of IT leaders say t he number of tools needed to monitor the end-to-end technology stack makes it difficult to operate efficiently. When issues arise, teams can’t depend on these tools for quick resolutions, because data comparisons are difficult and contribute to delays.

Government 147

Government Analytics Cloud Storage 147

Sutter's Mill

MARCH 11, 2024

tl;dr: I don’t want C++ to limit what I can express efficiently. Efficiency. The rules that are not efficient enough to implement in the compiler will always be relegated to optional standalone tools. That’s pretty easy to statically guarantee, except for some cases of the unused parts of lazily constructed array/vector storage.

C++ 139

C++ Programming Code Java 139

The Morning Paper

APRIL 16, 2019

Teaching rigorous distributed systems with efficient model checking Michael et al., During the ten week course, students implement four different assignments: an exactly-once RPC protocol; a primary-backup system; Paxos; and a scalable, transactional key-value storage system. EuroSys’19.

Systems 43

Systems Efficiency Testing Strategy 43

The Netflix TechBlog

FEBRUARY 13, 2020

By Aditya Mavlankar, Jan De C**k¹, Cyril Concolato, Kyle Swanson, Anush Moorthy and Anne Aaron TL; DR We need an alternative to JPEG that a) is widely supported, b) has better compression efficiency and c) has a wider feature set. High-Efficiency Video Coding ( HEVC ) is the successor of H.264, 264, a.k.a.

Code 212

Code Metrics Efficiency Open Source 212

O'Reilly

SEPTEMBER 19, 2023

It progressed from “raw compute and storage” to “reimplementing key services in push-button fashion” to “becoming the backbone of AI work”—all under the umbrella of “renting time and storage on someone else’s computers.” ” (It will be easier to fit in the overhead storage.)

Hardware 99

Hardware Storage Big Data Blockchain 99

IO River

NOVEMBER 2, 2023

They need to deliver impeccable performance without breaking the bank.According to recent industry statistics, global streaming has seen an uptick of 30% in the past year, underscoring the importance of efficient CDN architecture strategies. This is where a well-architected Content Delivery Network (CDN) shines. The result?

Architecture 52

Architecture Performance Internet Internet 52

The Netflix TechBlog

NOVEMBER 2, 2021

Perceptual quality measurements are used to drive video encoding optimizations , perform video codec comparisons , carry out A/B testing and optimize streaming QoE decisions to mention a few. Video quality has matured in Cosmos and we are invested in making VQS more flexible and efficient.

Media 171

Media Innovation Metrics Latency 171

Percona

MARCH 30, 2023

Further, open source databases can be modified in infinite ways, enabling institutions to meet their specific needs for data storage, retrieval, and processing. Non-relational databases: Instead of tables, non-relational (NoSQL) databases use document-based data storage, column-oriented storage, and graph databases.

Open Source 73

Open Source Database Storage Scalability 73

IO River

NOVEMBER 2, 2023

They need to deliver impeccable performance without breaking the bank.According to recent industry statistics, global streaming has seen an uptick of 30% in the past year, underscoring the importance of efficient CDN architecture strategies. This is where a well-architected Content Delivery Network (CDN) shines. Only overflow will await you.Â

Architecture 52

Architecture Performance Internet Internet 52

HammerDB

JUNE 27, 2022

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. Derived Workloads. Cached vs Scaled Workloads.

Benchmarking 62

Benchmarking Open Source C++ Cache 62

Testsigma

DECEMBER 1, 2020

It consists of a combination of right practices and tools which help QA to test the software more effectively and efficiently. Building an efficient testing automation framework takes time but it is worth the efforts considering the long-term benefits. How to Build a Test Automation Framework from Scratch.

Testing 62

Testing Website DevOps Mobile 62

Dynatrace

SEPTEMBER 25, 2019

Citrix is a sophisticated, efficient, and highly scalable application delivery platform that is itself comprised of anywhere from hundreds to thousands of servers. Dynatrace automation and AI-powered monitoring of your entire IT landscape help you to engage your Citrix management tools where they are most efficient. Dynatrace news.

Latency 117

Latency Performance Virtualization Infrastructure 117

Particular Software

SEPTEMBER 20, 2021

It’s less of an apples-to-oranges comparison and more like apples-to-orange-sherbet. Meanwhile, the garbage collector (or whatever manages memory in your runtime environment) is trying to make things efficient by cleaning up memory that’s not used anymore. But the answer isn’t that simple. Let’s take a look at the bigger picture. ??

Benchmarking 97

Benchmarking Latency Servers Systems 97

Percona

JULY 3, 2023

Hash keys are used effectively and efficiently in cases where ranges are not applicable, like employee number, product ID, etc. What if the data is out of range or list? For this purpose, we use default partitions on range and list partitioned tables. Further details will be explained in upcoming blogs.

Storage 80

Storage Database Performance Open Source 80

Highly Scalable

APRIL 2, 2012

Categories can contain thousands of products and user cannot efficiently search though this array without powerful tools. The rationale behind these methods is that frontend should be able to fetch transient information very efficiently and separately from fetching of heavy-weight domain entities because this information cannot be cached.

Ecommerce 100

Ecommerce Cache Storage Architecture 100

Highly Scalable

SEPTEMBER 18, 2012

These developments gradually highlight a system of relevant database building blocks with proven practical efficiency. In comparison with pure anti-entropy, this greatly improves consistency with a relatively small performance penalty. System Coordination. It can be considered as a kind of targeted anti-entropy.

Database 213

Database Latency C++ Scalability 213

SQL Performance

SEPTEMBER 5, 2019

This table uses columnstore for its primary storage to produce batch mode execution later on. Here is the new SUM plan for comparison with the one from the first test: All 102,400 rows (in 114 batches) are emitted by the Columnstore Index Scan , processed by the Compute Scalar , and sent to the Hash Aggregate. c1 = @Start + N.

Performance 81

Performance C++ Storage Servers 81

SQL Performance

MAY 8, 2019

Fellow SQL Server MVP Paul White theorizes that it could be related to using information from the outer input’s leaf to hint the storage engine to avoid duplicated effort by the read-ahead mechanisms. They’re also quite efficient, using a Left Semi Join optimization with a short-circuit. You can find the details here. So far, so good.

Best Practices 68

Best Practices C++ Code Servers 68

The Morning Paper

MAY 28, 2019

One efficient way of doing that in analog hardware is the use of current-starved inverters. The evaluation is performed using the MNIST dataset, since that has the most results available in the literature for comparison. One such possible representation is pure analog signalling. Performance evaluation.

Energy 52

Energy Hardware Efficiency Architecture 52

Highly Scalable

MARCH 1, 2012

In this article I provide a short comparison of NoSQL system families from the data modeling point of view and digest several common modeling techniques. And this was where a new evolution of data models began: Key-Value storage is a very simplistic, but very powerful model. 10) Inverted Search – Direct Aggregation.

Database 279

Database Ecommerce Efficiency Engineering 279

SQL Performance

AUGUST 23, 2019

Bloom filters present a space- and time-efficient alternative when a simple bitmap is infeasible due to space requirements. This is much less efficient than segment elimination or filtering during the columnstore scan, but it is still better than filtering at the hash join itself. LTGT for a less than/greater than comparison).

Servers 75

Servers Engineering Efficiency Retail 75

Highly Scalable

MAY 1, 2012

On the other hand, when one is interested only in simple additive metrics like total page views or average price of conversion, it is obvious that raw data can be efficiently summarized, for example, on a daily basis or using simple in-stream counters. bits per unique value. Frequency Estimation: Count-Min Sketch.

Analytics 191

Analytics Traffic Big Data Efficiency 191