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New analytics capabilities for messaging system-related anomalies

Dynatrace

In serverless and microservices architectures, messaging systems are often used to build asynchronous service-to-service communication. Messaging systems are typically implemented as lightweight storage represented by queues or topics. – DevOps Engineer, large healthcare company. This is great! New to Dynatrace?

Analytics 189
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. The Greenplum Architecture.

Big Data 321
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Causal AI use cases for modern observability that can transform any business

Dynatrace

Healthcare. For example, causal AI can help public health officials better understand the effects of environmental factors, healthcare policies, and social factors on health outcomes. Data lakehouses combine a data lake’s flexible storage with a data warehouse’s fast performance.

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What Is PostgreSQL Used For?

Percona

It’s used for data management (shocker), application development, and data analytics. PostgreSQL has powerful and advanced features, including asynchronous replication, full-text searches of the database, and native support for JSON-style storage, key-value storage, and XML. What is PostgreSQL used for?

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The Ultimate Guide to Open Source Databases

Percona

This comprehensive overview examines open source database architecture, types, pros and cons, uses by industry, and how open source databases compare with proprietary databases. Further, open source databases can be modified in infinite ways, enabling institutions to meet their specific needs for data storage, retrieval, and processing.

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Dutch Enterprises and The Cloud

All Things Distributed

Shell leverages AWS for big data analytics to help achieve these goals. Due to the exponential growth of the biology and informatics fields, Unilever needs to maintain this new program within a highly-scalable environment that supports parallel computation and heavy data storage demands.

Cloud 129