Category Archives: Object Storage

Is Dell Fluid Enough?

Dell made a huge splash 2 weeks ago in London in their inaugural Dell Storage Forum. They dubbed their storage and management lineup as “Fluid Data Architecture” offering the ability for customers to quickly adapt and automate their business when it comes to storage networking and more importantly, data management.

In the London show, they showcased several key innovations and product development. Here’s a list of their jewels:

  • DR4000 – an inline, content optimized backup deduplication appliance (based on the acquired technology of Ocarina Networks)
  • Compellent Storage Center 6.0 – a major software release
  • Compellent key technology integration with VMware
  • Optimized object storage for Microsoft Sharepoint with the DX6000 Object Storage Platform – DX6000 is an OEM from Caringo
  • Broader support for Dell Force10, PowerConnect and their partner’s Brocade

The technology from Ocarina Networks is fantastic technology and I have always admired Ocarina. I have written about Ocarina in the past in my previous blog. But I was a bit perplexed why Dell chose to enter the secondary dedupe market with a backup dedupe appliance in the DR4000. They are already a latecomer into the secondary deduplication game and I thought HP was already late with their StoreOnce.

They could have used Ocarina’s technology to trailblaze the primary deduplication market. In my previous blog, I mentioned that primary deduplication hasn’t really taken off in a big way, and Dell with the technology from Ocarina could set the standard and establish themselves as the leader of the primary deduplication market space. I was disappointed that they didn’t, not just yet.

The Compellent Storage Center 6.0 release was a major release and it was, for better or for worse, coincided with the departure of Phil Soran, the founder and CEO of Compellent. Phil felt that he can let his baby go and Dell is certainly making the best of what they can do with Compellent as their flagship data storage product.

The major release included 64-bit support for greater performance and scalability and also include several key VMware technologies that other vendors already have. The technologies included:

  • VMware vStorage API for Array Integration (VAAI)
  • Storage Replication Adapter plug-in for VMware Site Recovery Manager (SRM)
  • VSphere 5 client plug-in
  • Integration of Enterprise Manager and VSphere

Other storage related releases (I am not going to talk about Force10 or their PowerConnect solutions here) included Dell offering 16Gbps FibreChannel switches from Brocade and also their DX6000 Object Storage Platform optimized for Microsoft Sharepoint.

I think it is fantastic that Dell is adapting and evolving into a business-oriented, enterprise solution provider and their acquisitions in the past 3 years – EqualLogic, Exanet, Ocarina Networks, Force10 and Compellent – proves that Dell aims to take market share in the storage networking and data management market. They have key initiatives with CommVault, Symantec, VMware and Microsoft as well. And Michael Dell is becoming quite a celebrity lately, giving Dell the boost it needs to battle in this market.

But the question is, “Is their Fluid Data Architecture” fluid enough?” If I were a customer, would I bite?

As a customer, I look for completeness in the total solution, and I cannot fault Dell for having most of the pieces in the solution stack. They have networking in their PowerConnect, Force10 and Brocade. They have SAN in both Compellent and EqualLogic but their unified storage story is still a bit lacking. That’s because we have not seen Dell’s NAS storage yet. Exanet was a scale-out NAS and we have seen little rah-rah about this product.

From a data management perspective, their data protection story gels well with the Commvault and Symantec partnership, but I feel that Dell sales and SEs (at least in Malaysia) spends too much time touting the Compellent Automated Storage Tiering. I have spoken to folks who have listened to Dell guys’ pitches and it’s too one-dimensional. It’s always about storage tiering and little else about other Compellent technology.

At this point of time, the story that Dell sells here in Malaysia is still disjointed, but they are getting better. And eventually, the fluidity (pun intended ;-)) of their Fluid Data Architecture will soon improve.

How will Dell fare in 2012? They had taken a beating in the past 2 IDC’s quarter storage market tracker, losing some percentage points in market share but I think Dell will continue to tinker to get it right.

2012 will be their watershed year.

Captain Dynamo Storage System

My research on file systems brought me to an very interesting piece of article. It is titled “Dynamo: Amazon’s Highly Available Key-Value Store” dated 2007.

Yes, this is an internal storage systems designed and developed in Amazon to scale and support Amazon Web Services (AWS). It is a very complex piece of technology and the paper is highly technical (not for the faint of heart). And of all places, Amazon is probably the last place you think you would find such smart technology, but it’s true. AWS engineers are slowly revealing the many of their innovations (think Amazon Silk browser technology).

And it appears that many of the latest cloud-based computing and services companies such as Amazon, Google and many others have been developing new methods of storing data objects. These methods are very different from the traditional methods of storing data, and many are no longer adopting the relational database model (RDBMS) to scale their business.

The traditional 3-tier architecture often adopted by web-based (before the advent of “cloud”), is evolving. As shown in the diagram below:

the foundation tier is usually a relational database (or a distributed relational database), communicating with the back-end storage (usually a SAN).

All that is changing because the relational database model is not keeping up with the tremendous pace of the proliferation of web-based and cloud-based objects or unstructured data. As explained by Alex Iskold, a writer of ReadWriteWeb, there are scalability issues with the conventional relational database.

Before I get to the scalability issues mentioned in the above diagram, let me set the floor for discussion.

For theoretical schoolers of relational database, the term ACID defines and guarantees the transactional reliability of relational databases. ACID stands for Atomicity, Consistency, Isolation and Durability. According to Wikipedia, “transactions provide an “all-or-nothing” proposition, stating that each work-unit performed in a database must either complete in its entirety or have no effect whatsoever. Further, the system must isolate each transaction from other transactions, results must conform to existing constraints in the database, and transactions that complete successfully must get written to durable storage.”

ACID has been the cornerstone of relational database from the very beginning. But as the demands of greater scalability and greater distribution of data, all 4 components of ACID – Atomicity, Consistency, Isolation, Durability – can no longer hold true. Hence, the CAP Theorem.

CAP Theorem (aka Brewer’s Theorem) stands for Consistency, Availability and Partition Tolerance. In the ACM (Association of Computing Machinery) conference in 2000, Eric Brewer of University of California, Berkeley delivered the theorem. It states that it is impossible for a distributed computer system (or a database system) to simultaneously guarantee all 3 components – Consistency, Availability and Partition Tolerance.

Therefore, as the database systems become more and more distributed in cyberspace, the ACID theorem begins to break down. All 4 components of ACID cannot be guaranteed simultaneously anymore as the database systems begin to become more and more distributed.

So when we get back to the diagram, both the concepts on left and right – Master/Slave OR Multiple Peers – will put a tremendous strain on the single, non-distributed relational database.

New data models are surfacing to handling the very distributed data sets. Distributed object-based  “file systems” and NoSQL type of databases are some of the unconventional data storage “systems” that are beginning to surface as viable alternatives to the relational database method in cyberspace. And one of them is the Amazon Dynamo Storage System. (ADSS)

ADSS is a highly available, Amazon-proprietary key-value distributed data store. ADSS has both the properties of distributed hash table and a database and it is used internally to power various Cloud Services in Amazon Web Services (AWS).

It behaves like a relational database where it stores data objects to be retrieved. However, the data objects are not stored in a table format of a conventional relational database. Instead, the data is stored in a distributed hash table and data content or value is retrieved with a key, hence a key-value data model.

The data content is stored and retrieved through a simple put and get interface, much like how RESTful would do it. From the article in ReadWriteWeb, here’s how Dynamo works:

  • Physical nodes are thought of as identical and organized into a ring.
  • Virtual nodes are created by the system and mapped onto physical nodes, so that hardware can be swapped for maintenance and failure.
  • The partitioning algorithm is one of the most complicated pieces of the system, it specifies which nodes will store a given object.
  • The partitioning mechanism automatically scales as nodes enter and leave the system.
  • Every object is asynchronously replicated to N nodes.
  • The updates to the system occur asynchronously and may result in multiple copies of the object in the system with slightly different states.
  • The discrepancies in the system are reconciled after a period of time, ensuring eventual consistency.
  • Any node in the system can be issued a put or get request for any key


The Dynamo architecture addresses the CAP Theorem well. It is highly available, where nodes, either physical or virtual,  can be easily swapped without affected the storage services. It is also high performance, nodes (again physical or virtual) can be added to boost the performance. The high performance and highly available components addresses the “A” piece of CAP.

Its distributed nature also allows it to scale to billions and billions of data objects and hence meets the “P” requirement of CAP. The Partitioning Tolerance is definitely there.

However, as stated by CAP Theorem, you can’t have all 3 happening at the same time. Therefore, the “C” or Consistency piece of CAP has to be compromised. That is why Dynamo has been labeled an “eventually consistency” storage system.

As data is stored into ADSS, the changes of the data is propogated and will be asynchronously replicated to other nodes in the system, eventually making all the data objects and its value consistent. However, given the speed of things in cyberspace and the nature of most Cloud Computing services, the consistency piece could be difficult to accomplish and that is OK because in most of the transactions that are distributed, inconsistency is acceptable.

So that’s a bit about the Amazon Dynamo. Alas, we may never get our grubby hands on this piece of cool data storage and management technology, but knowing that Dynamo is powering AWS and its business is an eye-opener for us into the realm of a new technology evolution.

The future is intelligent objects

We are used to block-based approach and also the file-based approach to data. The 2 diagrams below shows the basics of how we access data in both block-based and file-based data on the storage device.


For block-based , the storage of the blocks is merely in arrays of unrelated contiguous blocks. For file-based, as seen below,


there is another layer of abstraction, and this is called the file system. But if you seen both diagrams above, there are some random numbers in light blue and that is to represent the storage device, the hard disk drive’s export of “containers” to the file system or the application that is accessing the storage device. This is usually the LBA (Logical Block Addressing), which is basically set of schematics that defines the locations on the hard disk drives. LBA tells the location of where the data is stored. For more information about LBA, check out this Wikipedia definition. But the whole idea is LBA is dumb. It is pretty much static and exported to file systems and applications so that these guys can do something with it.

There’s something brewing in the background since 1994 and it is one of the many efforts to make intelligent storage devices. This new object-based interface was part of the research project done by Carnegie-Mellon University (CMU). Initially, it was known as Network Attached Secure Disk (NASD) but eventually made its way to the working group in SNIA, and developing it for ANSI T10 INCITS standard. ANSI T10 is the guardian of all SCSI standards. This is called Object Storage Device (OSD). The SCSI architecture diagram below shows the layer where OSD resides.


The motivation for this simple: To make storage devices of today to do more computational work, in particularly I/O, relieving the hosts and the local systems to concentrate other computational processing work. And the same time, the local systems must have some level of interactivity and management between the storage object and the computational hosts.

In the diagram below which compares both block-based and OSD,

you can see the separation of file system management interface that is at the kernel-space of the local host/system and this is replaced by the OSD Management interface at the storage device.

What does this all mean? This means that using LBA type of addressing that we are familiar with in the block-based and file-based storage is no longer the way to go, because as I mentioned before, LBA is dumb.

OSD, in some way, replaces the LBA with OIDs (Object IDs). The existing local system and/or its file system will interact with the storage devices with OIDs and the OIDs links to its respective objects storage. And the object will carry a lot of metadata, that represents the object, giving it the intelligent and management capability of the object.


The prominence of the metadata in the OSD would mean that we can build much more intelligent systems in the future. The OIDs and the objects can be grouped together in a flat design or can be organized and categorized in a virtual, hierarchical model.

Object storage is an intelligent evolution of disk drives that can store and serve objects rather than simply place data on tracks and sectors. And it can bring the following benefits:

  • Intelligent space management in the storage layer
  • Data aware pre-fetching and caching
  • Robust shared access by multiple clients
  • Scalable performance using off-loaded data path
  • Reliability security
Several vendors such as EMC and NetApp are already supporting OSD.