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Kubernetes in the wild report 2023

Dynatrace

The report also reveals the leading programming languages practitioners use for application workloads. are the top 3 programming languages for Kubernetes application workloads. Redis is an in-memory key-value store and cache that simplifies processing, storage, and interaction with data in Kubernetes environments.

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DBaaS Pros & Cons

Scalegrid

A DBaaS automates several processes, such as using, erasing, and spinning up storage without interventions from IT staff. You don’t need to purchase additional storage when you have a self-managed cloud database. What happens if a change occurs but someone else is in the same program? Your data will always be intact.

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OpenShift vs. Kubernetes: Understanding the differences

Dynatrace

Kubernetes also gives developers freedom of choice when selecting operating systems, container runtimes, storage engines, and other key elements for their Kubernetes environments. Without having to worry about underlying infrastructure concerns, such as storage, security, and lifecycle management, developers can focus on writing code.

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Dutch Enterprises and The Cloud

All Things Distributed

Unilever – Unilever R&D program intended to accelerate the company’s scientific progress through improved access to global information. It makes use of the Eagle Genomics platform running on AWS, resulting in that Unilever’s digital data program now processes genetic sequences twenty times faster—without incurring higher compute costs.

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The Ultimate Guide to Open Source Databases

Percona

Further, open source databases can be modified in infinite ways, enabling institutions to meet their specific needs for data storage, retrieval, and processing. Non-relational databases: Instead of tables, non-relational (NoSQL) databases use document-based data storage, column-oriented storage, and graph databases.

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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Hosted on commodity clusters or cloud infrastructures, IMDGs harness the power of distributed computing to deliver scalable storage capacity and access throughput, along with integrated high availability. To help ensure fast data access and scalability, IMDGs usually employ a straightforward key/value storage model.

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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Hosted on commodity clusters or cloud infrastructures, IMDGs harness the power of distributed computing to deliver scalable storage capacity and access throughput, along with integrated high availability. To help ensure fast data access and scalability, IMDGs usually employ a straightforward key/value storage model.