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Choosing a cloud DBMS: architectures and tradeoffs

The Morning Paper

Which I’m quite happy to see as my most recent data pipeline is based around Lambda, S3, and Athena, and it’s been working great for my use case. For query executors that can be frequently started and stopped the authors explore performance with cold and warm caches (where applicable), and also the horizontal and vertical scaling performance.

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AWS serverless services: Exploring your options

Dynatrace

This means you no longer have to provision, scale, and maintain servers to run your applications, databases, and storage systems. Scalability. Finally, there’s scalability. Lambda functions can be written in the language of your choice, and the service also supports container tools. Data Store.

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AWS EKS Monitoring as a Self-Service with Dynatrace

Dynatrace

REDIS for caching. With the existing notification integrations for tools such as Slack, xMatters, ServiceNow, Lambda, JIRA, you can also pro-actively notify people in case there’s a problem: Dynatrace auto detected a problem with 3 kube proxies. Their technology stack looks like this: Spring Boot-based Microservices. 3 Log Analytics.

AWS 127
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Embrace event-driven computing: Amazon expands DynamoDB with streams, cross-region replication, and database triggers

All Things Distributed

I am excited to share with you that today we are expanding DynamoDB with streams, cross-region replication, and database triggers. Streams provide you with the underlying infrastructure to create new applications, such as continuously updated free-text search indexes, caches, or other creative extensions requiring up-to-date table changes.

Database 167
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In-Stream Big Data Processing

Highly Scalable

This article is an effort to explore techniques used by developers of in-stream data processing systems, trace the connections of these techniques to massive batch processing and OLTP/OLAP databases, and discuss how one unified query engine can support in-stream, batch, and OLAP processing at the same time.

Big Data 154
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Cloudburst: stateful functions-as-a-service

The Morning Paper

Last week we looked at a function shipping solution to the problem; Cloudburst uses the more common data shipping to bring data to caches next to function runtimes (though you could also make a case that the scheduling algorithm placing function execution in locations where the data is cached a flavour of function-shipping too).

Lambda 98
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A one size fits all database doesn't fit anyone

All Things Distributed

A common question that I get is why do we offer so many database products? To do this, they need to be able to use multiple databases and data models within the same application. Seldom can one database fit the needs of multiple distinct use cases. Seldom can one database fit the needs of multiple distinct use cases.

Database 167