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Spring Boot and Time Series Data in ScyllaDB

DZone

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 285
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Leveraging Infrastructure as Code for Data Engineering Projects: A Comprehensive Guide

DZone

Data engineering projects often require the setup and management of complex infrastructures that support data processing, storage, and analysis. In this article, we will explore the benefits of leveraging IaC for data engineering projects and provide detailed implementation steps to get started.

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Storage Autoscaling With Percona Operator for MongoDB

Percona

ViewBlock , a blockchain explorer, uses the Percona Operator for MongoDB to store critical data. Today along with their team, we will see how pvc-autoresizer can automate storage scaling for MongoDB clusters on Kubernetes. In our lab we will use AWS EKS with a standard storage class. Note : If you use version 1.14.0

Storage 109
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MongoDB Rollback: How to Minimize Data Loss

Scalegrid

When a MongoDB rollback happens, it can cause trouble to your data integrity and system consistency. Understanding how to address a rollback is critical for minimizing potential data loss and maintaining seamless operations. The consequences of rollbacks are significant and should not be underestimated.

Database 130
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Time Series Analysis: VAR-Model-As-A-Service Using Flask and MinIO

DZone

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 264
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The Power of Caching: Boosting API Performance and Scalability

DZone

Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing.

Cache 246
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Tuning EMQX To Scale to One Million Concurrent Connection on Kubernetes

DZone

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 305