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Showing entries 1 to 7

Displaying posts with tag: clustered database (reset)

Why You Should Embrace Database Virtualization
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This article addresses the benefits provided from database virtualization. Before we proceed however, it is important to explain that database virtualization does NOT mean simply running a DBMS inside a virtual machine.

Database Virtualization, More Than Running a DBMS in a Virtual MachineWhile running a DBMS in a VM can provide advantages (and disadvantages) it is NOT database virtualization. Typical databases fuse together the data (or I/O) with the processing (CPU utilization) to operate as a single unit. Simply running that single unit in a VM does not provide the benefits detailed below. That is not database virtualization that is merely server virtualization.
An Example of the Database Virtualization ProblemSay you have a database handling banking and I have $10MM in the bank (I wish). Now let’s assume that the bank is busy, so it


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Why You Should Embrace Database Virtualization
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This article addresses the benefits provided from database virtualization. Before we proceed however, it is important to explain that database virtualization does NOT mean simply running a DBMS inside a virtual machine. Database Virtualization, More Than Running a DBMS in a Virtual Machine While running a DBMS in a VM can provide advantages (and disadvantages) it is NOT database virtualization. Typical databases fuse together the data (or I/O) with the processing (CPU utilization) to operate as a single unit. Simply running that single unit in a VM does not provide the benefits detailed below. That is not database virtualization that is merely server virtualization.
An Example of the Database Virtualization Problem Say you have a database handling

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Database Virtualization, What it Really Means
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This is a response to a blog postby analyst and marketing consultant Curt Monash.
Originally virtualization meant running one operating system in a window inside of another operating system, e.g. running a Linux on a Windows machine using Microsoft Virtual PC or VMWare. Then virtualization evolved to mean slicing a single server into many for more granular resource allocation (Curt’s ex uno plures, translated: out of one, many). It has since expanded to include e pluribus unum (from many, one) and e pluribus ad pluribus (from many to many). This is evidenced in the use of the term “virtualization” to create the compound words: server virtualization, storage virtualization, network virtualization and now database virtualization.
Server


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Database Virtualization, What it Really Means
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This is a response to a blog postby analyst and marketing consultant Curt Monash. Originally virtualization meant running one operating system in a window inside of another operating system, e.g. running a Linux on a Windows machine using Microsoft Virtual PC or VMWare. Then virtualization evolved to mean slicing a single server into many for more granular resource allocation (Curt’s ex uno plures, translated: out of one, many). It has since expanded to include e pluribus unum (from many, one) and e pluribus ad pluribus (from many to many). This is evidenced in the use of the term “virtualization” to create the compound words: server virtualization, storage

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Lack of Business Visibility Cripples Traditional SQL DaaS, Drives NewSQL
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More and more public cloud companies are moving to managed cloud services to improve their value-add (price premium) and the stickiness of their solution. However, the shift to a database as a service (DaaS) severely reduces the DBAs visibility into the business, thus limiting the ability to hand tune the database to the requirements of the application and the database. The solution is a cloud database that eliminates the hand-tuning of the database, thereby enabling the DBA to be equally effective even with limited visibility into the business and application needs. It is these unique needs, particularly for SQL databases, that is fueling the NewSQL movement.
DBAs traditionally have insight into the company, enabling them to hand tune the database in a collaborative basis with the development team, such as:
1. Performance Trade-offs/Tuning: The database is

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The CAP Theorem Event Horizon
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The CAP Theorem has become a convenient excuse for throwing data consistency under the bus. It is automatically assumed that every distributed system falls prey to CAP and therefore must sacrifice one of the three objectives, with consistency being the consistent fall guy. This automatic assumption is simply false. I am not debating the validity of the CAP Theorem, but instead positing that the onset of CAP limitations—what I call the CAP event horizon—does not start as soon as you move to a second master database node. Certain approaches can, in fact, extend the CAP event horizon.
Physics tells us that different properties apply at different scales. For example, quantum physics displays properties that do not apply at larger scale. We see similar nuances in scaling databases. For example, if you are running a master slave database, using synchronous replication with a single
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ScaleDB Cache Accelerator Server (CAS): A Game Changer for Clustered Databases
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ScaleDB and Oracle RAC are both clustered databases that use a shared-disk architecture. As I have mentioned previously, they both actually share data via a shared cache, so it might be more appropriate to call them shared-cache databases.

Whether it is called shared-disk or shared-cache, these databases must orchestrate the sharing of a single set of data amongst multiple nodes. This introduces two challenges: the physical sharing of the data and the logical sharing of the data.

Physical Sharing:
Raw storage is meant to work on a 1:1 basis with a single server. In order to share that data amongst multiple servers, you need either a Network File System (NFS), which shares whole files, or a Cluster File System (CFS), which shares data blocks.






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Showing entries 1 to 7

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