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The Latest Databases Topics

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4 Spring Annotations Every Java Developer Should Know
Here are the most important Spring annotations that every Java developer should know.
July 1, 2019
by Justin Albano DZone Core CORE
· 68,486 Views · 67 Likes
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Ingesting Data From Apache Kafka to TimescaleDB
See how to ingest data from Apache Kafka to TimescaleDB.
June 28, 2019
by Pat Patterson
· 22,650 Views · 4 Likes
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JDBC Connection Pool In Payara Using phpMyAdmin (MySQL)
In this article, we will learn how to create a JDBC connection pool in PHPMyAdmin.
June 28, 2019
by Hitanshi Mehta
· 12,987 Views · 3 Likes
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DBMS_JOB — Watching for Failures
If you rely on jobs submitted via DBMS_JOB to fail, then read on.
June 28, 2019
by Connor McDonald
· 12,398 Views · 2 Likes
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Spring MVC and MongoDB: A Match Made in Platform.sh Heaven
Check out this post to learn more about Spring MVC and MongoDB on Platform.sh.
June 28, 2019
by Otavio Santana DZone Core CORE
· 15,617 Views · 4 Likes
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Table Inheritance: What's It Good For?
This post covers uses of table inheritance, which simplify overall database design.
June 27, 2019
by Chris Travers
· 20,875 Views · 2 Likes
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Asynchronous Communication With Queues and Microservices: A Perfect Combination?
In this article, we throw some light on what asynchronous messaging is all about and discuss why you should consider it for your microservices architectures.
June 27, 2019
by Ranga Karanam
· 26,863 Views · 8 Likes
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Making Your Microservices Resilient and Fault Tolerant
There are a number of things you can do to make sure that the entire chain of microservices does not fail with the failure of a single component. Let's dive in!
June 27, 2019
by Samir Behara
· 50,206 Views · 11 Likes
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Bulk Geocode Addresses Using Google Maps and GeoPy
Learn how to ingest and analyze big data sets of geographical coordinates with Python.
Updated June 26, 2019
by Cedric Brun
· 33,079 Views · 2 Likes
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Uploading and Downloading Files: Buffering in Node.js
In this post, we'll learn how to perform file uploads and downloads using buffered binds and fetches.
Updated June 26, 2019
by Dan McGhan
· 40,419 Views · 1 Like
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Smart Pipes and Smart Endpoints With Service Mesh
We look into some of the fallacies surrounding distributed computing and how service mesh helps address them.
June 26, 2019
by Samir Behara
· 11,498 Views · 6 Likes
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Firebase vs. MongoDB: Which Database to Use for Your App Development
MongoDB vs. Firebase. A comparison between the best NoSQL databases to find the best one for your app development project.
Updated June 26, 2019
by Paresh Sagar
· 89,260 Views · 7 Likes
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An Angular PWA From Front-End to Backend: Kubernetes Deployment
This tutorial shows how to deploy a Angular PWA on a Kubernetes cluster with a Helm Chart.
June 26, 2019
by Sven Loesekann
· 14,394 Views · 2 Likes
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Microservice Best Practices: Build an Archetype
In this article, we focus on learning why creating proper archetypes is important for a successful microservices architecture.
June 26, 2019
by Ranga Karanam
· 18,752 Views · 6 Likes
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AWS Workflow With PyCharm
Avoid some of the snafus of creating a workflow using AWS Toolkits with this tutorial.
June 26, 2019
by Marco Christiani
· 11,222 Views · 3 Likes
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7 Strategies for Assigning Ids to Microservices
In this article, we'll discuss seven strategies for assigning Ids and their trade-offs.
June 25, 2019
by Victor Chircu
· 24,488 Views · 14 Likes
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Oracle vs. Snowflake
Take a look at Oracle vs. Snowflake from someone who has worked for both.
Updated June 25, 2019
by John Ryan
· 20,687 Views · 5 Likes
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The 4 AWS Pricing Principles with a Critical Eye
Amazon Web Services advertises four principles that guide their pricing strategy - pay as you go, pay less by using more, save when you reserve, and their free tier. These principles provide immense benefits and efficiencies for thousands of organizations, which has driven AWS’s stellar growth. But there are downsides as well. In this article we'll review the five principles and provide a grain of salt you should consider before hooking into the Amazon machine. Principle #1: Pay as You Go The Principle: This is the main idea behind AWS - instead of buying or building costly infrastructure, rent it. AWS is dedicated to turning your CapEx expenses into OpEx. It also provides extreme flexibility - you can order 1,000 machines for an hour and then stop them and pay only for those 1,000 machine hours. The Good: It’s why organizations started moving to the cloud. Pay per use is great because it eliminates overcapacity and wasted computing resources. The Bad: Flexibility comes at a cost. If you want to really “pay as you go”, you’ll have to settle for Amazon’s On-Demand Pricing, which becomes quite expensive even for small workloads, when used for ongoing server deployments. Truth be told, most servers don’t have huge peaks or troughs in their usage - and running them on dedicated hosting or on-prem will be a lot cheaper than on Amazon. Principle #2: Pay Less by Using More The Principle: AWS provides volume discounts. Amazon S3 and many other services offer tiered pricing, and Amazon EC2 offers volume discounts for users who spend more than $500,000 in upfront costs. Amazon also provides a plethora of services and options for most use cases, allowing you to switch to a service that meets your need at a lower cost. For example, there are several AWS backup options including the AWS Backup service and storage services like S3, Glacier, EBS, EFS, etc. Organizations can move data between these storage services to gain efficiencies. The Good: Sophisticated users of AWS can save a lot by dynamically moving workloads between services and creating economies of scale. The Bad: This principle is also one of the hidden reasons for Amazon’s enormous complexity. True - you can create a tiered storage strategy and save 90% or more in many cases. But do your engineers or IT staff know the intricacies of each data service, and have the know-how to detect the relevant events and store data selectively into different data stores? Amazon provides the tools to do all this. But it requires time and expertise which by itself costs organizations serious money. Principle #3: Save When You Reserve The Principle: At the core of AWS is its compute service, Amazon EC2. EC2 machine instances are substantially discounted (on the order of 30-50%) if you reserve an instance for 1-3 years in advance. Another option is to use “spot instances” - machine instances that happen to be available at a given time, and will be taken away from you when another user demands them. Switching loads dynamically between spot instances, and helping Amazon manage their demand, can give you even bigger discounts. The Good: Amazon provides a lot of price flexibility. You can significantly cut costs by committing to 1 years or more - it’s possible to do this selectively for some workloads, while using others on demand. The spot instances option is a creative one, which lets anyone with expertise, and the time to architect a spot instances solution, shave 60% off costs. The Bad: Committing to a machine instance for 1 to 3 years on the cloud might sound like an oxymoron. Organizations are moving to the cloud to get computing resources on demand. A long-term financial commitment flies in the face of this flexibility. Many AWS users take on-demand prices as a given, and pay the price of flexibility. Principle #4: Free Usage Tier The Principle: Amazon grants 1 year of free usage with generous quotas for many of its services, to reduce risk and encourage cloud adoption. This was a primary way AWS gained its initial market share in the early years. The Free Tier Grants (as of the time of this writing) 1 year of usage with 750 hours of EC2 instances, 750 hours of RDS usage (can run managed databases like MySQL), 5 GB on S3, 1 million requests on the cool serverless delivery platform Lambda, 50 GB storage on CloudFront (delivery network), 5GB on EFS (file storage), 30GB on EBS (block storage), 750 hours of ElasticSearch, and more. The Bad: The free tier has helped many organizations and technologists get “hooked” on Amazon’s offerings - it is a showcase of the astounding depth, breadth and technical excellence of their service profile. Amazon provides - and encourages - an enormous amount of sophistication within its ecosystem. It provides power, but power brings with it responsibility, overhead and a high cost of skills. Very often, organizations select AWS by default because it is a market leader and the option most well known by their teams. I can’t say the free tier is bad, but it has creatd an unfair advantage vs. other cloud offerings, which have their own strengths. Wrap Up AWS is great, but it is also a business and has established pricing that safeguards its interests. Carefully consider the benefits and tradeoffs of the Amazon pricing philosophy before entering a large-scale engagement. If you're already heavily engaged, plan your cloud consumption 1-2 years ahead and see if other cloud platforms - such as Azure or Google Cloud Platform - can give Amazon a run for its money.
Updated June 25, 2019
by Gilad David Maayan
· 23,175 Views · 2 Likes
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Develop a REST API in PHP
Feeling tired? Read on to get some REST.
June 25, 2019
by Aaron Parecki
· 34,717 Views · 3 Likes
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Inserting BLOB Values With SQL INSERT Statements
This article describes how to insert BLOB values as normal strings using INSERT statements.
June 25, 2019
by Mark Rules
· 56,285 Views · 4 Likes
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