ScaleOut Software

JULY 21, 2020

For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache. Designed to help scalable applications deliver high performance, it stores live, fast-changing data in memory (DRAM) for fast updates and retrieval. The Challenges with Parallel Queries.

Analytics 52

Analytics Airlines Cache Scalability 52

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 Scalability Architecture 130

The Morning Paper

JUNE 16, 2019

Therefore, frontend code is responsible for permission checks and privacy-preserving transformations that protect user’s data. 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. Recent research has provided this missing key primitive.

Database 90

Database Cache Benchmarking Efficiency 90

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. Scalability. Finally, there’s scalability.

Serverless 285

Serverless AWS Lambda Storage 285

ScaleOut Software

APRIL 22, 2020

The Solution: Distributed Caching. The solution to this challenge is to use scalable, memory-based data storage for fast-changing data so that web sites can keep up with exploding workloads. It’s not enough simply to lash together a set of servers hosting a collection of in-memory caches.

Cache 52

Cache Storage Servers Database 52

ScaleOut Software

APRIL 22, 2020

The Solution: Distributed Caching. The solution to this challenge is to use scalable, memory-based data storage for fast-changing data so that web sites can keep up with exploding workloads. It’s not enough simply to lash together a set of servers hosting a collection of in-memory caches.

Cache 52

Cache Storage Servers Database 52

High Scalability

JULY 20, 2018

Cliff Click : The JVM is very good at eliminating the cost of code abstraction, but not the cost of data abstraction. That means multiple data indirections mean multiple cache misses. Mark LaPedus : MRAM, a next-generation memory type, is being touted as a replacement for embedded flash and cache applications.

Internet 121

Internet Internet Scalability Automotive 121

Percona

MAY 15, 2023

This operation is quite expensive but our database can run it in a few milliseconds or less, thanks to several optimizations that allow the node to execute most of them in memory with no or little access to mass storage. As well, very few cases are in need to have a full system/solution to provide scalability with sharding.

Traffic 124

Traffic Scalability Database Servers 124

The Morning Paper

FEBRUARY 6, 2020

Last week we looked at a function shipping solution to the problem; Cloudburst uses the more common data shipping to bring data to caches next to function runtimes (though you could also make a case that the scheduling algorithm placing function execution in locations where the data is cached a flavour of function-shipping too).

Serverless 98

Serverless Lambda Cache Latency 98

Percona

JULY 17, 2023

DBAs and developers appreciate its combination of flexibility, scalability, and performance. Organizations have access to the source code, allowing them to make changes and enhancements as needed. Storing large datasets can be a challenge, as Redis’ storage capacity is limited by available RAM. Couchbase — No.

Open Source 76

Open Source Database Scalability Software 76

HammerDB

JUNE 27, 2022

HammerDB is Free software and consequently engineers should consider not only how they can benefit from using the software but also how they can contribute to the community with code and documentation. Cached vs Scaled Workloads. Instead, most users prefer to implement a cached workload.

Benchmarking 62

Benchmarking Open Source C++ Cache 62

ScaleOut Software

JULY 27, 2018

Hosted on commodity clusters or cloud infrastructures, IMDGs harness the power of distributed computing to deliver scalable storage capacity and access throughput, along with integrated high availability. To help ensure fast data access and scalability, IMDGs usually employ a straightforward key/value storage model.

Scalability 40

Scalability Cache Airlines Healthcare 40

ScaleOut Software

JULY 27, 2018

Hosted on commodity clusters or cloud infrastructures, IMDGs harness the power of distributed computing to deliver scalable storage capacity and access throughput, along with integrated high availability. To help ensure fast data access and scalability, IMDGs usually employ a straightforward key/value storage model.

Scalability 40

Scalability Cache Airlines Healthcare 40

All Things Distributed

JUNE 21, 2017

Today, I'm excited to announce the general availability of Amazon DynamoDB Accelerator (DAX) , a fully managed, highly available, in-memory cache that can speed up DynamoDB response times from milliseconds to microseconds, even at millions of requests per second. DynamoDB was the first service at AWS to use SSD storage.

Speed 121

Speed Cache Latency AWS 121

ScaleOut Software

MAY 15, 2014

We have spent a great deal of time at ScaleOut Software re-architecting our in-memory data grid (IMDG)’s code base to make best use of many cores and large memory. For example, the IMDG must be able to efficiently create millions of objects in each server to make use of its huge storage capacity. Please retry later.

Cache 40

Cache Servers Network Design 40

Highly Scalable

AUGUST 20, 2013

The pipelines can be stateful and the engine’s middleware should provide a persistent storage to enable state checkpointing. In many cases join is performed on a finite time window or other type of buffer e.g. LFU cache that contains most frequent tuples in the stream. Interoperability with Hadoop.

Big Data 154

Big Data Processing Lambda Database 154

Smashing Magazine

JUNE 25, 2020

It’s not just source code for the configuration, models, views, and templates, but also static assets: CSS and JavaScript, images, icons. Today, we’ll address storing and serving files for both single-server and scalable deployments while considering factors like compression, caching, and availability. Philip Kiely.

Media 70

Media Cache Storage AWS 70

The Morning Paper

SEPTEMBER 10, 2019

When each of those use cases is powered by a dedicated back-end, investments in better performance, improved scalability and efficiency etc. Cache all the things. Procella achieves high scalability and efficiency by segregating storage (in Colossus) from compute (on Borg). are divided. Making Procella fast.

Analytics 75

Analytics Latency Cache Google 75

IO River

NOVEMBER 2, 2023

‍Before we dive into what Terraform is, let's begin with a real-world example of how Terraform code looks and works:‍# Challenge requests coming from known Tor exit nodes.‍‍In Background‍The idea of managing infrastructure through code wasn't initiated by HashiCorp. ‍Why Manage Infrastructure by Code?‍‍If

Open Source 52

Open Source DevOps AWS Infrastructure 52

All Things Distributed

JUNE 21, 2018

As I have talked about before, one of the reasons why we built Amazon DynamoDB was that Amazon was pushing the limits of what was a leading commercial database at the time and we were unable to sustain the availability, scalability, and performance needs that our growing Amazon.com business demanded. The opposite is true.

Database 167

Database AWS Games Latency 167

IO River

NOVEMBER 2, 2023

Before we dive into what Terraform is, let's begin with a real-world example of how Terraform code looks and works:‍# Challenge requests coming from known Tor exit nodes.‍‍In the example above, we're using Terraform to set up an access rule on Cloudflare. This rule challenges requests coming from known Tor exit nodes.

Open Source 40

Open Source DevOps AWS Infrastructure 40

All Things Distributed

APRIL 27, 2011

Werner Vogels weblog on building scalable and robust distributed systems. To our shareowners: Random forests, naïve Bayesian estimators, RESTful services, gossip protocols, eventual consistency, data sharding, anti-entropy, Byzantine quorum, erasure coding, vector clocks. Driving Storage Costs Down for AWS Customers.

Technology 151

Technology Technology AWS Storage 151

Abhishek Tiwari

NOVEMBER 3, 2018

An SSG offers a middle ground between a complex yet modular CMS solution and a simple yet involved hand-coded HTML site. Alternatively, you can upload output directory to cloud object/blob storage such as Amazon S3 or Azure Blob Storage and serve your site from there. Eventually, we decided to move them to Jekyll.

Systems 63

Systems Cache Website Network 63

Percona

JUNE 22, 2023

It also supports the flexibility and scalability of the database infrastructure. Flexibility : With open source databases, you have access to the source code, allowing you to modify and optimize the database to meet your specific high availability requirements. This flexibility can be crucial in designing a scalable architecture.

Availability 106

Availability Database Open Source Hardware 106

SQL Server According to Bob

JANUARY 11, 2020

Time of Last Access The time of last access is a caching ​​ algorithm ​​ that enables ​​ cache ​​ entries to be ordered by their ​​ access times.

Servers 40

Servers Cache Database Media 40

Enprowess

JANUARY 12, 2022

So it is convenient for all to use irrespective of internet speed and it works offline using cached data. Easy Deployment: PWAs can be deployed easily using a single code base that runs on accelerated mobile pages and web browsers. Blockchain technology is an encrypted database storage system. Famous PWA Use Examples.

Blockchain 59

Blockchain IoT Development Serverless 59

Smashing Magazine

JANUARY 11, 2021

Have we optimized enough with tree-shaking, scope hoisting, code-splitting, and all the fancy loading patterns with intersection observer, progressive hydration, clients hints, HTTP/3, service workers and — oh my — edge workers? It’s much easier to reach performance goals when the code base is fresh or is just being refactored.

Performance 145

Performance Cache Media Metrics 145

Smashing Magazine

JANUARY 6, 2020

Is it worth exploring tree-shaking, scope hoisting, code-splitting, and all the fancy loading patterns with intersection observer, server push, clients hints, HTTP/2, service workers and — oh my — edge workers? It’s much easier to reach performance goals when the code base is fresh or is just being refactored.

Performance 145

Performance Cache Network Metrics 145

High Scalability

NOVEMBER 25, 2019

It is limited by the disk space; it can’t expand storage elastically; it chokes if you run few I/O intensive processes or try collaborating with 100 other users. Over time, costs for S3 and GCS became reasonable and with Egnyte’s storage plugin architecture, our customers can now bring in any storage backend of their choice.

Architecture 52

Architecture Cache Azure Storage 52

Smashing Magazine

JANUARY 7, 2019

Is it worth exploring tree-shaking, scope hoisting, code-splitting, and all the fancy loading patterns with intersection observer, server push, clients hints, HTTP/2, service workers and — oh my — edge workers? The first render tends to warm up a bunch of lazily compiled code, which a larger tree can benefit from when it scales.

Performance 104

Performance Cache Metrics Network 104