Dynatrace
JANUARY 16, 2023
Most Kubernetes clusters in the cloud (73%) are built on top of managed distributions from the hyperscalers like AWS Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE). Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch.
Scalegrid
MAY 13, 2020
When handling large amounts of complex data, or big data, chances are that your main machine might start getting crushed by all of the data it has to process in order to produce your analytics results. Greenplum features a cost-based query optimizer for large-scale, big data workloads. Query Optimization.
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Abhishek Tiwari
DECEMBER 22, 2017
Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. You can also use cloud and SaaS services such as Google BigQuery, Amazon Redshift Spectrum, Amazon Athena, Qubole to implement ELT approach.
Rigor
SEPTEMBER 11, 2019
Jake is a developer advocate at Google working with the Chrome team to develop and promote web standards and developer tools, as well as a contributor to the Chromium blog. Jake is a frequent speaker at many popular conferences and events, such as 100 Days of Google Dev , JAMstakConf , JSConf , SmashingConf , and dozens of others.
The Agile Manager
FEBRUARY 27, 2012
The rise of Big Data - the ability to store and analyze large volumes of structured and unstructured, internal and external data - promises to let companies react more nimbly than ever before. Fashion magazines are launching electronic retail sites. Apple is now in the greeting card business, Google in travel.
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