Architecture, Big Data, Efficiency and Scalability

What is Greenplum Database? Intro to the Big Data Database

Scalegrid

MAY 13, 2020

In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. It’s architecture was specially designed to manage large-scale data warehouses and business intelligence workloads by giving you the ability to spread your data out across a multitude of servers.

Big Data

Big Data Database Artificial Intelligence Open Source

What is a Distributed Storage System

Scalegrid

FEBRUARY 8, 2024

Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. Variations within these storage systems are called distributed file systems.

Storage

Storage Systems Big Data Azure

Redis vs Memcached in 2024

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

Cache Storage Scalability Architecture

Mastering Hybrid Cloud Strategy

Scalegrid

MARCH 14, 2024

This approach allows companies to combine the security and control of private clouds with public clouds’ scalability and innovation potential. Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. A hybrid cloud strategy could be your answer.

Strategy

Strategy Cloud Artificial Intelligence Infrastructure

What is IT operations analytics? Extract more data insights from more sources

Dynatrace

MAY 1, 2023

In addition to improved IT operational efficiency at a lower cost, ITOA also enhances digital experience monitoring for increased customer engagement and satisfaction. Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information.

Analytics

Analytics Artificial Intelligence Big Data Open Source

In-Stream Big Data Processing

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. The engine should be compact and efficient, so one can deploy it in multiple datacenters on small clusters. High performance and mobility. Pipelining.

Big Data

Big Data Processing Lambda Database

Conducting log analysis with an observability platform and full data context

Dynatrace

APRIL 20, 2023

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. Further, business leaders must often determine whether the data is relevant for the business and if they can afford it.

Analytics

Analytics Infrastructure Storage Efficiency

Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

OCTOBER 4, 2022

Several pain points have made it difficult for organizations to manage their data efficiently and create actual value. Limited data availability constrains value creation. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes.

Analytics

Analytics Artificial Intelligence Storage Serverless

What is cloud monitoring? How to improve your full-stack visibility

Dynatrace

JANUARY 11, 2023

As cloud and big data complexity scales beyond the ability of traditional monitoring tools to handle, next-generation cloud monitoring and observability are becoming necessities for IT teams. Hybrid cloud combines an on-premises or private data center with public cloud infrastructure. What is cloud monitoring?

Cloud

Cloud Monitoring Best Practices Infrastructure

How Netflix uses eBPF flow logs at scale for network insight

The Netflix TechBlog

JUNE 7, 2021

By collecting, accessing and analyzing network data from a variety of sources like VPC Flow Logs , ELB Access Logs, eBPF flow logs on the instances, etc, we can provide network insight to users and central teams through multiple data visualization techniques like Lumen , Atlas , etc. What is BPF?

Network

Network Transportation AWS Cloud

What is container orchestration?

Dynatrace

MARCH 24, 2023

Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services. Apache Mesos with the Marathon DC/OS is popular for large-scale production clusters running existing workloads on big data systems, such as Hadoop, Kafka, and Spark.

Infrastructure

Infrastructure Open Source Operating System Cloud

The Need for Real-Time Device Tracking

ScaleOut Software

JULY 19, 2021

Today’s streaming analytics architectures are not equipped to make sense of this rapidly changing information and react to it as it arrives. This data is also periodically uploaded to a data lake for offline batch analysis that calculates key statistics and looks for big trends that can help optimize operations.

IoT

IoT Analytics Big Data Architecture

Current status, needs, and challenges in Heterogeneous and Composable Memory from the HCM workshop (HPCA’23)

ACM Sigarch

MAY 31, 2023

Introduction Memory systems are evolving into heterogeneous and composable architectures. Heterogeneous and Composable Memory (HCM) offers a feasible solution for terabyte- or petabyte-scale systems, addressing the performance and efficiency demands of emerging big-data applications. About application transparency.

Latency

Latency Hardware Cache Architecture

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High Scalability

APRIL 14, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education

Education Software Engineering Scalability Engineering

Post: InterviewCamp.io, Scrapinghub, Fauna, Sisu, Educative, PA File Sight, Etleap, Triplebyte, Stream

High Scalability

APRIL 28, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education

Education Software Engineering Scalability Engineering

Use Digital Twins for the Next Generation in Telematics

ScaleOut Software

NOVEMBER 24, 2020

Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks. Rapid advances in the telematics industry have dramatically boosted the efficiency of vehicle fleets and have found wide ranging applications from long haul transport to usage-based insurance.

Analytics

Analytics Architecture Scalability Software Architecture

Fast key-value stores: an idea whose time has come and gone

The Morning Paper

JUNE 23, 2019

The stateless + RInk (S+RInK) architecture attempts to provide the best of both worlds: to simultaneously offer both the implementation and operational simplicity of stateless application servers and the performance benefits of servers caching state in RAM. We’ve seen similar high marshalling overheads in big data systems too.)

Cache

Cache Latency Google Lambda

The Winds of Architecture Changes at the USENIX ATC 2019

ACM Sigarch

NOVEMBER 1, 2019

This blog post gives a glimpse of the computer systems research papers presented at the USENIX Annual Technical Conference (ATC) 2019, with an emphasis on systems that use new hardware architectures. As a consequence, the vast majority of the papers in the past has usually focused on conventional X86 or GPU-accelerated architectures.

Architecture

Architecture Hardware Cache Storage

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Netflix TechBlog

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Infrastructure

Infrastructure Big Data Transportation Architecture

Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

NOVEMBER 20, 2023

We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. IPS provides the incremental processing support with data accuracy, data freshness, and backfill for users and addresses many of the challenges in workflows. past 3 hours or 10 days).

Processing

Processing Big Data Efficiency Engineering

Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

OCTOBER 18, 2022

As Big data and ML became more prevalent and impactful, the scalability, reliability, and usability of the orchestrating ecosystem have increasingly become more important for our data scientists and the company. Meson was based on a single leader architecture with high availability.

Java

Java Scalability Traffic Architecture

Bulldozer: Batch Data Moving from Data Warehouse to Online Key-Value Stores

The Netflix TechBlog

OCTOBER 27, 2020

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. The processed data is typically stored as data warehouse tables in AWS S3. Moving data with Bulldozer at Netflix.

Latency

Latency Storage Big Data Tuning

Optimizing data warehouse storage

The Netflix TechBlog

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage

Storage Latency Efficiency Data Engineering

Data Mining Problems in Retail

Highly Scalable

MARCH 10, 2015

However, there are a number of other important applications: Manufacturer-sponsored discounts can fall into this category because a retailer is not concerned about the cost of the incentives (covered by the manufacturer), only about efficient targeting. RE94] Grouplens: an open architecture for collaborative filtering of netnews, P.

Retail

Retail C++ Analytics Metrics

Amazon EC2 Cluster GPU Instances - All Things Distributed

All Things Distributed

NOVEMBER 15, 2010

Werner Vogels weblog on building scalable and robust distributed systems. These trade-offs have even impacted the way the lowest level building blocks in our computer architectures have been designed. All Things Distributed. Expanding the Cloud - Adding the Incredible Power of the Amazon EC2 Cluster GPU Instances. Comments ().

AWS

AWS Latency Programming Architecture

Streaming SQL in Data Mesh

The Netflix TechBlog

NOVEMBER 3, 2023

The Data Mesh SQL Processor is a platform-managed, parameterized Flink Job that takes schematized sources and a Flink SQL query that will be executed against those sources. By leveraging Flink SQL within a Data Mesh Processor, we were able to support the streaming SQL functionality without changing the architecture of Data Mesh.

Processing

Processing Engineering Infrastructure Latency

Technology Performance Pulse

What is Greenplum Database? Intro to the Big Data Database

What is a Distributed Storage System

Trending Sources

Redis vs Memcached in 2024

Mastering Hybrid Cloud Strategy

What is IT operations analytics? Extract more data insights from more sources

In-Stream Big Data Processing

Conducting log analysis with an observability platform and full data context

Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

What is cloud monitoring? How to improve your full-stack visibility

How Netflix uses eBPF flow logs at scale for network insight

What is container orchestration?

The Need for Real-Time Device Tracking

Current status, needs, and challenges in Heterogeneous and Composable Memory from the HCM workshop (HPCA’23)

Post: InterviewCamp.io, Scrapinghub, Fauna, Sisu, Educative, PA File Sight, Etleap, Triplebyte, Stream

Sponsored Post: InterviewCamp.io, Scrapinghub, Fauna, Sisu, Educative, PA File Sight, Etleap, Triplebyte, Stream

Post: InterviewCamp.io, Scrapinghub, Fauna, Sisu, Educative, PA File Sight, Etleap, Triplebyte, Stream

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Use Digital Twins for the Next Generation in Telematics

Fast key-value stores: an idea whose time has come and gone

The Winds of Architecture Changes at the USENIX ATC 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

Incremental Processing using Netflix Maestro and Apache Iceberg

Orchestrating Data/ML Workflows at Scale With Netflix Maestro

Bulldozer: Batch Data Moving from Data Warehouse to Online Key-Value Stores

Optimizing data warehouse storage

Data Mining Problems in Retail

Amazon EC2 Cluster GPU Instances - All Things Distributed

Streaming SQL in Data Mesh

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