Remove Azure Remove Big Data Remove Latency Remove Monitoring
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ScyllaDB Trends – How Users Deploy The Real-Time Big Data Database

Scalegrid

ScyllaDB offers significantly lower latency which allows you to process a high volume of data with minimal delay. percentile latency is up to 11X better than Cassandra on AWS EC2 bare metal. Azure followed in third place representing 17.4% Azure followed in third place representing 17.4% The remaining 13.0%

Big Data 187
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No need to compromise visibility in public clouds with the new Azure services supported by Dynatrace

Dynatrace

As adoption rates for Microsoft Azure continue to skyrocket, Dynatrace is developing a deeper integration with the platform to provide even more value to organizations that run their businesses on Azure or use it as a part of their multi-cloud strategy. Azure Batch. Azure DB for MariaDB. Azure DB for MySQL.

Azure 150
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What is a Distributed Storage System

Scalegrid

Opting for synchronous replication within distributed storage brings about reinforced consistency and integrity of data, but also bears higher expenses than other forms of replicating data. By implementing data replication strategies, distributed storage systems achieve greater.

Storage 130
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

Agent and open technologies make it easy to ingest large volumes of observability, security, and business data. Data management. Data lakehouses take advantage of low-cost object stores like AWS S3 or Microsoft Azure Blob Storage to store and manage data cost-effectively. Data warehouses. Query language.

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Mastering Hybrid Cloud Strategy

Scalegrid

Workloads from web content, big data analytics, and artificial intelligence stand out as particularly well-suited for hybrid cloud infrastructure owing to their fluctuating computational needs and scalability demands.

Strategy 130
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The Need for Real-Time Device Tracking

ScaleOut Software

And it can maintain contextual information about every data source (like the medical history of a device wearer or the maintenance history of a refrigeration system) and keep it immediately at hand to enhance the analysis. Conventional streaming analytics architectures have not kept up with the growing demands of IoT.

IoT 78