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Data Science

▾ 0 MINUTE READ — CLOSE

The era of the single-use database is over and we are seeing a plethora of new database systems built for specific tasks (distributed key value stores, NewSQL,graph databases, etc). Over the next few years there will be some shakeout in the industry as enterprises decide between the tradeoff of performance that the new databases bring versus the ease-of-use that more general use databases (MySQL, PostgreSQL) offer.

Of particular note is the emergence of streaming data, which requires data to be analyzed while still in the server’s memory. Here, Kafka and other technologies supplant the traditional Hadoop and Spark-based big data tools.  Also, there is the ongoing challenge of fitting stateful database workloads into “stateless” cloud-native architectures.


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Data Science / IoT Edge Computing / Machine Learning
Lenovo Bulks up Its Edge Server Portfolio for AI
13 Dec 2021 11:42am, by Jeffrey Burt
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Cloud Native Ecosystem / Cloud Services / Data Science / Security / Technology / Sponsored
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How to Select the Right Database for Time-Series Data
2 Dec 2021 7:38am, by Jane Fine
Data Science / Kubernetes / Networking
Confluent Platform 7.0: Data Streaming Across Multiclouds
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17 Nov 2021 6:15am, by Miles Adkins
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Distributed SQL Takes Databases to the Next Level
15 Nov 2021 11:32am, by Rob Hedgpeth
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JSON Custom Data Types Come to Excel Spreadsheets
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