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Solution
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Situation
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Benefits
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Key Components
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Consolidating Mixed Workloads Read Solution Brief
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- Increase in database and server sprawl
- Larger workload footprints
- Greater cost and complexity running workloads on siloed IT
- Longer maintenance and upgrade cycles
- Inefficient copy data management
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- Maximize valuable datacenter floor space with a smaller footprint
- Lower database licensing costs with fewer instances of the database software
- Manage CAPEX and OPEX at scale
- Deliver predictable performance at scale for mixed Microsoft SQL Server workloads
- Provision copies at the speed of the business through greater agility
- Improve backup and disaster recovery through centralization
- Ensure application-driven data protection and long term backup retention
- Enable cloud operating model efficiency and savings
- Strive for “Always On” in the digital era
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Reference Architecture
- PowerEdge Modular Server
- PowerMax Storage
- Data Domain DD Boost for Enterprise Applications
- Data Domain Storage
Hyperconverged Infrastructure
- Storage Spaces Direct Ready Node
Converged Infrastructure
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Running SQL on Linux Read Reference Architecture Guide
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- Adoption of cloud operating model
- Move towards a data-driven intelligent enterprise
- Expansion into containerization and open source
- Standardize operating model for production and test / development environments
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- Drive greater throughput on large complex Microsoft SQL Server queries
- Accelerate decision support analysis
- Scale under increasing Microsoft SQL Server workloads while providing strong storage performance
- Deliver consistently low latencies for accessing database data
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Reference Architecture
- PowerEdge Servers
- XtremIO All-Flash Storage
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Microsoft SQL Migrations and Upgrades Read Solution Overview
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- Microsoft SQL Server 2008/R end of support
- Invest in hybrid cloud operating model
- Incorporate meaningful insights into decision-making process
- Make Microsoft SQL Server data available in a timely, relevant and actionable manner
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- Evaluate Microsoft SQL Server database environment to identify potential areas for performance improvement.
- Improve data quality with a modernized data landscape
- Design and implement resilient Microsoft SQL Server data architectures for on-premises, off-premises and hybrid cloud strategies
- Assess and plan for future business requirements
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Dell Technologies Consulting Services Reference Architecture
- PowerEdge Modular Server
- PowerMax Storage
- XtremIO X2 All-Flash Storage
- Unity XT All-Flash Storage
- Data Domain DD Boost for Enterprise Applications
- Data Domain Storage
Hyperconverged Infrastructure
- Storage Spaces Direct Ready Node
- Cloud for Microsoft Azure Stack
Converged Infrastructure
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Microsoft SQL Server 2019 Containers Read White Paper
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- Difficult to manage and ensure code and data consistency between RDBMS and applications
- Containers are reshaping how companies think about developing, deploying, and maintaining applications and software
- Concerns over lack of support for persistent storage of database files separate from ephemeral container files
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- Quickly and easily deploy applications and databases consistently across multiple environments
- Deliver secure, isolated development and test environments in seconds
- Create persistent storage for stateful applications
- Simplify provisioning, management and orchestration of container storage
- Improve productivity and simplify application portability
- Spend more time building new applications and competitive business services
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Reference Architecture
- PowerEdge Modular Server
- XtremIO X2 All-Flash Storage
Hyperconverged Infrastructure
- VxFlex Integrated Rack
- VxFlex Appliance
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Microsoft SQL Server 2019 Big Data Clusters Read White Paper
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- IoT and connected devices are generating volumes of data that are exceeding the storage capacity of traditional database systems
- Inability to quickly and easily access all types of data, locked within storage silos, to perform business analysis and reporting
- IoT data sets are unstructured and without business context, often in formats that are not suitable for storing in relational database tables or for querying using relational query semantics
- Inefficient extract, transform, load (ETL) processes inhibits near real-time analysis.
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- Enable intelligence over all your data
- Remove the limitations created from data silos by combining both structured and unstructured data across the entire data estate
- Deploy scalable clusters using Apache Spark, HDFS containers with Kubernetes, and SQL Server
- Deliver secure, isolated virtualized containers quickly and easily
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Hyperconverged Infrastructure
- VxFlex Integrated Rack
- VxFlex Appliance
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