San Mateo, Calif.-based storage provider Cloudian has announced it has raised $94 million in a series E funding round, a good indication of the booming enterprise storage market and possible validation for an idea called “object storage.” This also implies, however, that enterprise storage users are slowly and steadily tiring of solutions that offer only incrementally more performance and scale.
The technology they’re tiring of is called block storage — the process of splitting up files into evenly sized blocks of data, each with its own address but with no additional information. The additional information we’d like to have here is called metadata and it serves to provide more context into what that block of data is. You’re likely to encounter block storage in the majority of enterprise workloads.
The problem with object storage is that as more and more data is generated, storage systems have to “physically” keep up at the same pace. This means adding more “blocks” to a system that was never built with the intention of dealing with data on this scale in the first place. Additionally, when you cross the hundred terabyte or petabyte region, hard limitations with storage infrastructure, durability issues, and increasing management overhead is what most people run into.
Object storage, on the other hand, doesn’t split files up into raw blocks of data but instead stores an entire “clump” of data as an object. An object consists of three parts, the actual data, metadata, and the unique identifier which is an address given to the object in order for the object to be found over a distributed system. This way it really doesn’t matter where the data exists, within the data center or on the other side of the planet.
What makes object storage so powerful and customizable is that there is no limit on the type or amount of metadata and it can include anything from file security classifications to the importance of an application associated with that file. Additionally, scaling out object storage architectures is as simple as adding additional nodes. This is mainly thanks to the simple and efficient namespace organization of data, in combination with the aforementioned metadata functionality.
Items such as static web content, data backup, and archives are excellent use cases of object storage. In fact, anyone who’s ever stored a picture on Facebook or listened to a song on Spotify has already used object storage. In the enterprise, object storage is preferred where data needs to be both highly available and highly durable at the same time. A good example is Amazon S3, which stores data as objects within resources called “buckets.” S3 offers features like 99.999999999 percent durabilities, cross-region replication, event notifications, versioning, encryption, and flexible storage options.
Now since this technology was only available in the cloud, it was previously of little use to customers who need their data as close to home as possible. Cloudian’s hybrid approach, however, brings this cloud-like storage technology right to the source of the data where it’s really needed and not far away in some centralized cloud. The theory is simple yet efficient; the storage can be anywhere, period.
This is probably why Daniel Auerbach, senior managing partner at Eight Roads Ventures, was quoted as stating, “When Eight Roads Ventures first invested in Cloudian in 2014 we saw a different approach — here was a company applying cloud-scale technologies to the enterprise storage challenge.” The hybrid cloud approach he’s talking about here is Cloudian’s global enterprise storage fabric and its unique ability to let you push any data to the public cloud, while also affording you the control that comes with on-premises storage.
It does this with the help of a software-defined storage platform that transforms standard servers and virtual machines into a pool of logical storage resources. These resources can be located absolutely anywhere and are scalable to hundreds of petabytes and more. Additionally, the Cloudian architecture creates a global network of storage assets that form a hyperscale fabric that allows all resources to be pooled and shared over any distance.
Earlier this year, Cloudian set its sights on three trends driving the rise of object storage in 2018. The first of which is the growth of artificial intelligence and the Internet of Things and the second, massive data growth. The third is the rise of Amazon S3’s API as an industry standard.
With regards to target No. 3, Amazon’s S3 API is the de-facto standard for object storage APIs. This not only makes it easier to interchange between service providers, software providers, and their application standards but also rapidly facilitates new uses for object storage.
There are different grades of S3 compatibility, however, and while some software and solutions provide only the basic CRUD (create, remove, update, delete) functions. At the other end of the spectrum is Cloudian’s Hyperstore, that goes beyond the basic CRUD and features advanced APIs like versioning, multipart upload, access control list, and location constraint.
Cloudian has also added four additional areas to make S3 object storage enterprise-ready. Namely, Software or Appliance (not a service), APIs for all functions, O&M tools and Integration with other products. Being 100 percent S3 compatible is a big part of Cloudian’s vision and Paul Turner, chief marketing officer at Cloudian, was quoted as stating “Cloudian HyperStore delivers the best S3 compatibility among all object storage products.”
Now with regards to Cloudian’s three-pronged attack into the future, machine learning and the IoT factor in a big way, according to Cloudian CEO Michael Tso. “Cloudian’s unique architecture offers the limitless scalability, simplicity and cloud integration needed to enable the next generation of computing driven by advances such as IoT and machine learning technologies,” Tso says.
Data is the lifeblood of AI and machine learning, so what use is Big Data if not to train AI models? In fact, data has never been more valuable than it is today and from security cameras to sensors to smartphones, everything is always generating valuable data. So it’s unsurprising that companies that have this much data now want to use it for machine learning too. Late last year, Cloudian teamed with Skymind to create data management solutions for the hyper-scalable data sets necessary for artificial intelligence and machine learning use cases.
The partnership effectively translates to Cloudian’s limitlessly scalable on-premises storage systems teamed up with Skymind’s Deeplearning4j. The latter is especially useful at recognizing patterns in massive amounts of data so as to provide actionable intelligence. The two companies have been collaborating on integrated, enterprise-ready AI/ML solutions for a little over a year.
Investors in this round included Digital Alpha, Fidelity Eight Roads, Goldman Sachs and more and is probably the largest we have seen for a storage vendor. This brings the total funding to $173 million and Cloudian plans to use the new funding to expand its global sales and marketing efforts, as well as increase its engineering team. Michael Tso put it quite simply, stating, “We have to innovate in new areas like AI.” With Cloudian positioning itself quite nicely to exploit trends that are causing giants like $5.5 billion NetApp to shrink, the future looks especially bright for this storage vendor.
Featured image: Pixabay
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