cloud

Getting Started with Azure Cosmos DB & Entity Framework

Azure Cosmos DB is Microsoft’s globally distributed, multi-model database service. Cosmos DB enables you to elastically and independently scale throughput and storage across any number of Azure regions worldwide.

Setting Up Databases on Kubernetes

Kubernetes now supports StatefulSets and CRDs, one of the next logical steps is to run databases on it. But why should I do that in the first place? How hard is it? What are the challenges? Is it production ready?

Best Practices for Oracle Databases Cloud Migration

Oracle databases remain a major part of the application stack in many organizations. These days, it is no longer necessary to spend time and money installing, operating, monitoring and backing up your database. In this webinar, you will learn how Amazon Relational Database Service (RDS) and AWS Database Migration Service (DMS) make it easy to …

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Analyzing Billions of Data Rows

Got lots of data? So does Amaysim, a leading Australian telecom provider, with its billions of rows of data. The organization successfully empowers its small team of data analysts with self-service data analytics platforms so they can easily access the data they need, perform advanced analytics, and visualize findings for all stakeholders.

Build a Data Lake on Amazon Cloud

Conceptually, a data lake is a flat data store to collect data in its original form, without the need to enforce a predefined schema. Instead, new schemas or views are created “on demand”, providing a far more agile and flexible architecture while enabling new types of analytical insights. AWS provides many of the building blocks …

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Big Data Architectural Patterns and Best Practices

The world is producing an ever increasing volume, velocity, and variety of big data. Consumers and businesses are demanding up-to-the-second (or even millisecond) analytics on their fast-moving data, in addition to classic batch processing. AWS delivers many technologies for solving big data problems. But what services should you use, why, when, and how?