Why You Should Embrace Database Virtualization

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 banking and I have $10MM in the bank (I wish). Now let’s assume that the bank is busy, so it bursts that database across 3 VM nodes in typical cloud-style.  Now each of those 3 nodes gets a command to wire out the full $10MM. Each node sees its balance at $10MM, so each one wires out the full amount, for a total wire transfer of $30MM…see the problem? In order to dynamically burst your database across nodes, you need a distributed locking mechanism so that all nodes see the same data and can lock other nodes from altering the same data independently. This sounds easy, but making it perform well is a massive undertaking. Only two companies have solved this problem: Oracle RAC and ScaleDB (for MySQL or MariaDB).

Defining Database Virtualization

• It should enable the application to talk to a single virtual instance of the database, when in fact there are N number of actual nodes acting over the data.
• It should separate the data processing (CPU) from the data (I/O) so that each can scale on demand and independently from the other.
• For performance it should enable the actual processing of the data to be distributed to the various nodes on the storage tier (function shipping) to achieve maximum performance. Note: in practice, this is similar to MapReduce.
• It should provide tiered caching, for performance, but also ensure cache coherence across the entire cluster.

Benefits of Database Virtualization

Higher Server Utilization: When the data is fused to the CPU, as a single unit, that one node is responsible for handling all usage spikes for its collection of data. This forces you to spit the data thinly, across many servers (siloes), forcing you to run each server at a low utilization rate. Database Virtualization decouples the data from the processing so that the spike in usage can be shared across many nodes on the fly. This enables you to run a virtualized database at a very high utilization rate.

Reduced Infrastructure Costs: Database virtualization enables you to use fewer servers, less power, less OS, tools, application licenses, network switches and storage, among other things.

Reduced Manpower Costs: Database virtualization simplifies the DBA’s job, since it uses only one schema and no sharding, it also simplifies backup processes, enabling the DBA to handle more databases. It reduces the application developer’s job because it eliminates code related to sharding: e.g. database routing, rebuilding relationships between shards (e.g. joins), and more. It also simplifies the network admin’s job because he manages fewer servers and they are identical.

Reduced Complexity: You only have a single database image, so elastically scaling up/down is simple and fast.

Increased Flexibility: Database virtualization brings the same flexibility to the database that server virtualization brings to the application tier. Resources are allocated and reallocated on the fly. If your usage profile changes, e.g. payroll one day, benefits the next, a virtual database uses the same shared infrastructure for any workload, while a traditional database does not.

Quality of Service: Since database images can move on the fly, without downtime, a noisy neighbor or noisy network is solved by simply moving the database to another node in your pool.

Availability: Unlike a traditional database, virtualized database nodes see all of the data, so they inherently provide failover for one another, addressing unplanned downtime. In regards to planned downtime, simply move the process to another server and take down the one that needs service, again without interruption.

Improved Performance: Because the pooled cache across the storage tier uses a Least Recently Used (LRU) algorithm, it can free up huge amounts of pooled cache to the then current workload, enabling near in-memory performance.  Also, as mentioned above, the distribution of processing to the storage tier enables high-performance parallel processing.

True database virtualization delivers a huge set of advantages that in many ways mirror the benefits server virtualization provides to applications. For this reason, we expect database virtualization to be the next big thing, following in the footsteps of server, storage and network virtualization.

Additional Resources:

ScaleDB Database Virtualization Page

Wikipedia

Database Virtualization, What it Really Means

This is a response to a blog post by 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 Virtualization: Abstracts the physical (servers), presenting it as a logical entity or entities. VMWare enables dividing single physical resources (compute or storage) into multiple smaller units (one-to-many), as well as combining multiple physical units into a single logical unit, which they call clustering (many-to-one). Since a clustered collection of physical servers can address a clustered collection of physical storage devices, it therefore also supports the many-to-many configuration. If we extract the essence of virtualization it is the ability to address compute and storage resources logically, while abstracting the underlying physical representation.

This modern definition of virtualization is also evident in the following terms:

Storage Virtualization: Splitting a single disk into multiple virtual partitions (one-to many), a single logical view that spans multiple physical disks (RAID) and splitting multiple disks, often for high-availability, across multiple logical storage devices (mirroring or LUNs).  see also Logical Volume Management. 

Network Virtualization: “In computing, network virtualization is the process of combining hardware and software network resources and network functionality into a single, software-based administrative entity, a virtual network.” This is a many-to-one model. 

Virtual IP Addresses: This enables the application to have a single IP address that actually maps to multiple NICs. 

So this brings us to the topic of defining “Database Virtualization”. We believe that the most comprehensive description of database virtualization is the abstracting from physical resources (compute, data, RAM) to the logical representation, supporting many-to-one, one-to-many and many-to-many relationships. This is exactly what ScaleDB does better than any other database company, and this is why we are considered leaders in the nascent field of database virtualization.

ScaleDB provides a single logical view (of a single database) while that database is actually comprised of a cluster of multiple database instances operating over shared data. Whether you call this many-to-one (many database nodes acting as one logical database) or one-to-many (one logical database split across many nodes) is a matter of perspective. In either case, this enables independent scaling of both compute and I/O, eliminating the need for painful sharding, while also supporting multi-tenancy.

Curt then puts words in our mouths stating that we claim: “Any interesting database topology should be called “database virtualization”.” We make no such a claim. In fact, we state very clearly on our database virtualization page: “Database virtualization means different things to different people; from simply running the database executable in a virtual machine, or using virtualized storage, to a fully virtualized elastic database cluster composed of modular compute and storage components that are assembled on the fly to accommodate your database needs.”

In the marketing world, perception is reality. Since people are making claims of providing database virtualization, it is only prudent to include and compare their products, in a comprehensive evaluation of the space. Just as Curt addresses many things that are not databases (e.g. Memcached) in order to provide the reader with a comprehensive understanding, so do we when talking about database virtualization. One need only consider that we include “running the database executable in a virtual machine” as one of the approaches that some consider to be “database virtualization.” While we consider our approach to be the best solution for database virtualization, ignoring what other people consider to be database virtualization would have displayed extreme hubris on our part.

We appreciate Curt shining the light on database virtualization and we agree that it is “a hot subject right now.” It is a new field and therefore requires a comprehensive evaluation of all claims and approaches, enabling customers to decide which is the best approach for their needs. We remain quite confident that we will continue to lead the database virtualization market based upon our architectural advantages.

As the database virtualization market heats up, and as we enhance our solution set, we remain confident that Curt and other analysts will come to appreciate our unique advantages in this market.