In the News

Big data skills gap 'not huge' and even 'exaggerated' say Rackspace and EMC

The supposed IT skills gap that requires "10,000 data scientists" to fill is "exaggerated", claims storage vendor EMC, while Rackspace describes the figure as "aspirational".

These statements came from a big-data roundtable hosted by Rackspace, at which EMC solutions principal Bernd Kaponig said: "I think from my perspective it's not a huge skills gap, it's exaggerated."

MongoDB-Chef Schireson: Die Zeit relationaler Datenbanken läuft ab

In einem Interview mit ZDNet machte MongoDB-Chef Max Schireson deutlich, warum die Uhr für relationale Datenbankmanagementsysteme (RDBMS) tickt.

Die relationalen Datenbankmanagementsysteme haben rund 40 Jahre auf dem Buckel. Das ist eine lange Zeit, in der äußerst viel Wissen aufgebaut wurde und hundertausende Menschen sich intensiv mit RDBMS beschäftigt haben. Das schafft große Beharrungskräfte. Auch wenn ein RDBMS das falsche Tool für eine Aufgabe sein sollte, stehen die Chancen immer noch gut dafür, dass trotzdem ein RDBMS für den Job eingesetzt werden wird, meint MongoDB-Chef Max Schireson im Interview mit ZDNet. Er sagt, dass relationale Datenbanken für ganz andere Umgebungen und Anforderungen gebaut worden sind. "Man hatte ein Jahr Zeit, eine Anwendung zu entwickeln, kannte die Datenbasis, sie hatte kleinere und gleichförmigere Datasets und die fertige Anwendung durfte zu Wartungszwecken noch abgeschaltet werden. All das und vieles mehr hat sich heute geändert. Als Lösungsvorschläge wurden die Produkte der NoSQL-Datenbanken entwickelt, deren laut DB-Engine-Ranking beliebtester Vertreter das Open-Source-Produkt MongoDB derzeit ist. Es liegt als beliebtestes NoSQL-System auf Platz 5.

Big data skills gap 'not huge' and even 'exaggerated' say Rackspace and EMC

... Owen believes that big data platforms are becoming easier for end users to operate without the need for new skillsets. He cited the example of MongoDB, which, though it only started in 2007, is now "one of the top-10 databses in the world".

"But how many people have become experts in it in that time?" he asked.

"It's competing very well with established relational databases that are 40 years old. I think that makes a point for getting help [now] - vendors provide help, and service providers have a place for concentrating knowledge. Not every company is going to be able to afford to hire data scientists or a MongoDB DA [data analyst]."...

MongoDB chief: Why the clock's ticking for relational databases

On top of business's growing frustration with proprietary software, the relational database model championed by the big vendors is looking increasingly dated, according to the CEO of leading open-source NoSQL database MongoDB.

Relational databases go back to an era before the internet and are now ill suited to the demands of the cloud and high user numbers, Max Schireson said.

"The database market is in need of a big change. The technology that people typically use, the database layer, was designed in 1970 with a very different set of requirements in mind," he said.

Datasets in those days were smaller and more uniform, and development processes were more waterfall with requirements well known in advance.

"You'd spend a year or two building your application, and then you could revise it. Applications didn't need to be live all the time," Schireson said.

Security and governance key concerns as big data becomes mainstream

Security and data governance are the main challenges facing firms embracing big data projects in 2014, according to key players in the industry speaking at a roundtable event hosted by Rackspace and attended by V3. However, data security and governance are likely to become significant issues, as cloud services figure prominently in most big data strategies.

There is still plenty of hype around big data, with analyst firm IDC predicting that the market for this will be worth an estimated $16.1 billion in 2014 and experience a growth rate six times that of the rest of the IT market.

IBM's Acquisition of Cloudant and the Walmart Effect In Tech

... The acquisition of Cloudant will be central to IBM's MobileFirst solutions as well as its Worklight application for developing mobile applications. From an industry perspective, the acquisition represents a huge coup for the NoSQL space in general. CouchDB has historically not had the traction of MongoDB, Cassandra and Couchbase, so we should expect brand name tech companies to make similar offerings for the likes of MongoDB in the ensuing few months. Moreover, IBM's acquisition of Cloudant testifies to the increasing emergence of cloud and big data behemoths with solutions for both hosting infrastructure, as well as database solutions that accommodate enterprise needs for scalability and the ability to store unstructured data....

SharesPost 100 List

The SharesPost 100 is our list of what we think are the very best late-stage venture-backed private growth companies.

In assembling the SharesPost 100 list each quarter, SharesPost leverages a proprietary multi-factor ranking process that incorporates criteria including, but not limited to:

Revenue growth
Market potential
Product stage
Management team
Investor quality

The result? Our list of a veritable who's who of some of the world's most innovative, compelling private companies.

Is it finally time to integrate a NoSQL solution into your enterprise apps?

... A NoSQL solution doesn't rely on data laid out in an orderly fashion in tables that are all linked closely together in a relational manner, which is the standard SQL based approach. With tables, users have the ability to carry out very refined and detailed queries to extract data in the form of reports. However, SQL databases can be cumbersome to maintain—especially as the amount of data increases exponentially. And a bigger problem than being difficult to maintain is the fact that they simply can't scale linearly beyond a certain point.

Kelly Stirman, Director of Product Marketing at MongoDB, describes why keeping data up-to-date in a traditional database can be a challenge. "The relational data model spreads data across many tables. There might be thousands of tables for one application. If you need to update an object in the data layer, you're coordinating the updating of data across many tables in one operation. You need sophisticated transactions to ensure the integrity of that update across many tables." Stirman says a NoSQL approach using document stores is less complex. "The data model is very different. Instead of trying to map a large, complex schema to objects, you have a direct mapping of documents to objects. Updating an object is as simple as updating a single document." ...

Big Data: Are you ready for blast-off?

For large businesses "the cost of data storage has plummeted," says Andrew Carr, UK and Ireland chief executive of IT consultancy Bull. Businesses can either keep all their data on-site, in their own remote data centres, or farm it out to "cloud-based" data storage providers.

A number of open source platforms have grown up specifically to handle these vast amounts of data quickly and efficiently, including Hadoop, MongoDB, Cassandra, and NoSQL.

Big Data : le concept de mieux en mieux compris, les projets en production à la hausse

Non seulement les entreprises comprennent mieux le Big Data , mais elles commencent également à structurer leur usage. C’est une des conclusions que l’on pourrait tirer de deux études publiées séparément en ce début 2014, l’une réalisée par JasperSoft auprès de sa communauté d’utilisateurs - très aguerris à la problématique Big Data et à leur usage dans l’analytique notamment - , et l’autre émanant du très populaire cabinet d’analystes Gartner. Le Big Data sort quelque peu de l’ombre pour prendre forme dans des projets concrets, faut-il ainsi comprendre.

Ainsi, si l’on en croit les chiffres récupérés auprès de la communauté Jaspersoft (1 600 utilisateurs dont 60% de développeurs), la compréhension du phénomène Big Data, et de ses implications sur le modèle économique, se seraient nettement améliorés l’année dernière, déclenchant, par effet direct, la mise en place de réels projets financés par les entreprises - et donc supportés par le management. Rangeant ainsi le Big Data aux côtés des technologies plus matures, capables d’attirer l’attention des DSI, pour la production - et non plus uniquement pour de simples prototypes.