DZone

MARCH 22, 2024

In today's data-driven world, businesses face numerous challenges when it comes to storing, securing, and analyzing vast amounts of information. Enter StoneFly , a leading provider of storage area network (SAN) and network-attached storage (NAS) solutions that aim to simplify your life and tackle complex business problems head-on.

Storage 177

Storage Scalability Development Infrastructure 177

DZone

SEPTEMBER 25, 2023

It is the second of a series of articles that is built on top of that project, representing experiments with various statistical and machine learning models, data pipelines implemented using existing DAG tools, and storage services, both cloud-based and alternative on-premises solutions.

Storage 258

Storage AWS Architecture Cloud 258

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

DZone

NOVEMBER 7, 2023

This is about how a cyber security service provider built its log storage and analysis system (LSAS) and realized 3X data writing speed, 7X query execution speed, and visualized management. Log Storage and Analysis Platform In this use case, the LSAS collects system logs from its enterprise users, scans them, and detects viruses.

Storage 216

Storage Speed Systems 216

Dynatrace

JANUARY 17, 2024

And an O’Reilly Media survey indicated that two-thirds of survey respondents have already adopted generative AI —a form of AI that uses training data to create text, images, code, or other types of content that reflect its users’ natural language queries. AI requires more compute and storage. AI performs frequent data transfers.

Strategy 223

Strategy Artificial Intelligence Storage Cloud 223

Dynatrace

APRIL 24, 2024

To transparently manage expectations and maintain trust with our customers, we expanded the Dynatrace SLA beyond accessing the user interface to cover the full range of relevant product categories, such as processing and retaining incoming data, accessing and working with data, and triggering automations.

Azure 242

Azure Infrastructure Metrics AWS 242

Dynatrace

DECEMBER 5, 2023

Streamline privacy requirements with flexible retention periods Data retention is a critical aspect of data handling, and it’s not just about privacy compliance—it’s about having the flexibility to optimize data storage times in Grail for your Dynatrace use cases.

Storage 167

Storage Healthcare Best Practices Speed 167

DZone

MARCH 29, 2023

Data migration is the process of moving data from one location to another, which is an essential aspect of cloud migration. Data migration involves transferring data from on-premise storage to the cloud. With the rapid adoption of cloud computing , businesses are moving their IT infrastructure to the cloud.

Best Practices 304

Best Practices Cloud Storage Data Engineering 304

DZone

OCTOBER 24, 2023

The ELK stack is an abbreviation for Elasticsearch, Logstash, and Kibana, which offers the following capabilities: Elasticsearch: a scalable search and analytics engine with a log analytics tool and application-formed database, perfect for data-driven applications.

Analytics 255

Analytics Storage Infrastructure Scalability 255

Scalegrid

FEBRUARY 1, 2024

Regarding MySQL backups , knowing how to secure your data is crucial. Dive in to uncover the essentials of different backup types, command-line tools, and strategic practices for robust data protection. MySQL is a popular open-source relational database management system for online applications and data warehousing.

Best Practices 130

Best Practices Storage Strategy Database 130

DZone

NOVEMBER 25, 2023

We often dwell on the technical aspects of database selection, focusing on performance metrics , storage capacity, and querying capabilities. Factors like read and write speed, latency, and data distribution methods are essential. In a detailed article, we've discussed how to align a NoSQL database with specific business needs.

Database 268

Database Latency Speed Metrics 268

DZone

SEPTEMBER 14, 2023

In today's data-driven world, efficient data processing plays a pivotal role in the success of any project. Apache Spark , a robust open-source data processing framework, has emerged as a game-changer in this domain.

Big Data 269

Big Data Processing Games Open Source 269

Dynatrace

OCTOBER 17, 2023

In today’s data-driven landscape, businesses are grappling with an unprecedented surge in data volume. The data generated by applications to support operational teams has reached overwhelming proportions. This data overload also prevents customer-centric pricing models as users consider cost-effective technology platforms.

Retail 238

Retail Storage Best Practices Architecture 238

Dynatrace

MARCH 6, 2024

They create an explosion of data that is extremely challenging to manually capture, analyze, and act on. In fact, 81% of technology leaders say the effort their teams invest in maintaining monitoring tools and preparing data for analysis steals time from innovation. But these environments are, by nature, difficult to manage.

Analytics 192

Analytics Innovation Strategy Storage 192

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 288

Storage Cache Metrics Database 288

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

Scalegrid

MAY 13, 2020

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Scalegrid

JULY 17, 2020

It is an open standard format which organizes data into key/value pairs and arrays detailed in RFC 7159. JSON is the most common format used by web services to exchange data, store documents, unstructured data, etc. You can also check out our Working with JSON Data in PostgreSQL vs. JSONB Patterns & Antipatterns.

Storage 321

Storage Database Efficiency Processing 321

Dynatrace

JANUARY 31, 2024

Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. However, there are many obstacles and limitations along the way to becoming a data-driven organization. Understanding the context.

Analytics 195

Analytics Processing Transportation Storage 195

Dynatrace

APRIL 19, 2023

ALLOW storage:buckets:read WHERE storage:bucket-name startsWith “default_”;ALLOW storage:events:read, storage:logs:read, storage:metrics:read, storage:entities:read, storage:bizevents:read, storage:spans:read; Storage Read per table Each table includes a policy that combines table and bucket access called Storage <tablename> Read.

Storage 211

Storage Analytics Systems Architecture 211

DZone

JULY 13, 2023

In today's data-driven world, organizations need efficient and scalable data pipelines to process and analyze large volumes of data. Medallion Architecture provides a framework for organizing data processing workflows into different zones, enabling optimized batch and stream processing.

Azure 246

Azure Architecture Efficiency Processing 246

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

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 210

Artificial Intelligence Analytics Storage Government 210

DZone

FEBRUARY 23, 2023

Introduction With big data streaming platform and event ingestion service Azure Event Hubs , millions of events can be received and processed in a single second. Any real-time analytics provider or batching/storage adaptor can transform and store data supplied to an event hub.

Azure 294

Azure Big Data Analytics Storage 294

Dynatrace

APRIL 28, 2023

Optimize cost and availability while staying compliant Observability data like logs and metrics provide automated answers, root cause detection, and security issues. Customer decisions about data retention are often determined by important security, privacy, and legal issues.

Analytics 215

Analytics Storage Infrastructure Metrics 215

Dynatrace

NOVEMBER 9, 2023

Nutanix overview dashboard The extension automatically gathers real-time performance data from your Nutanix clusters to monitor resource usage, cluster health, and more, all in one place. Storage container metrics Track the usage and performance of storage containers to optimize resource allocation.

Virtualization 194

Virtualization Storage Metrics Monitoring 194

DZone

AUGUST 29, 2023

It is the first of a series of articles that will be built on top of that project, representing experiments with various statistical and machine learning models, data pipelines implemented using existing DAG tools, and storage services, both cloud-based and alternative on-premises solutions.

Storage 258

Storage Cloud 258

Dynatrace

OCTOBER 4, 2022

Some time ago, at a restaurant near Boston, three Dynatrace colleagues dined and discussed the growing data challenge for enterprises. At its core, this challenge involves a rapid increase in the amount—and complexity—of data collected within a company. Work with different and independent data types. Thus, Grail was born.

Artificial Intelligence 269

Artificial Intelligence Analytics Storage Architecture 269

Dynatrace

NOVEMBER 6, 2023

Cloud-native workloads on edge devices are gaining momentum among organizations as they extend the hybrid cloud closer to the data source and end users at the edge. The challenge of cloud-native observability at the enterprise edge In aggregate, connected devices generate huge volumes of data.

Retail 260

Retail Analytics Storage Metrics 260

DZone

JUNE 6, 2023

When building an IoT-based service, we need to implement a messaging mechanism that transmits data collected by the IoT devices to a hub or a server. When dealing with IoT, one of the first things that come to mind is the limited processing, networking, and storage capabilities these devices operate with.

IoT 293

IoT Tuning Storage Network 293

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

DZone

MAY 7, 2023

The following tutorial walks you through how to use Spring Boot apps with ScyllaDB for time series data, taking advantage of shard-aware drivers and prepared statements. ScyllaDB is used to store the stock price (time series data). And you’ll learn how ScyllaDB can be used to store time series data.

Storage 273

Storage Servers Testing 273

Dynatrace

OCTOBER 6, 2023

Grail: Enterprise-ready data lakehouse Grail, the Dynatrace causational data lakehouse, was explicitly designed for observability and security data, with artificial intelligence integrated into its foundation. Tables are a physical data model, essentially the type of observability data that you can store.

Artificial Intelligence 263

Artificial Intelligence Analytics Metrics Storage 263

DZone

APRIL 11, 2023

Data processing in the cloud has become increasingly popular due to its scalability, flexibility, and cost-effectiveness. This article will explore how these technologies can be used together to create an optimized data pipeline for data processing in the cloud.

Azure 246

Azure Analytics Storage Cloud 246

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 236

Analytics Artificial Intelligence Storage Serverless 236

Dynatrace

OCTOBER 23, 2023

Hyper-V plays a vital role in ensuring the reliable operations of data centers that are based on Microsoft platforms. Secondly, determining the correct allocation of resources (CPU, memory, storage) to each virtual machine to ensure optimal performance without over-provisioning can be difficult. What is Microsoft Hyper-V?

Efficiency 216

Efficiency Virtualization Hardware Performance 216

Dynatrace

JANUARY 4, 2024

While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. But to be successful, data quality is critical. Teams need to ensure the data is accurate and correctly represents real-world scenarios. Consistency.

Government 201

Government Analytics Benchmarking Storage 201