The most important thing about’s new data service might be its scale CEO Marc Benioff (pictured above) has always talked about his company as a cloud computing provider, but as popular as its applications have been, Salesforce has never operated at the same scale as its infrastructure-based cousins such as Amazon Web Services or Google. However, things might be about to change thanks to a new data analytics service, called Wave, that the company is announcing on Monday.

The new service, which is underpinned by a search-like, massively parallel processing architecture, represents a “dramatic expansion” of the company’s data center footprint, according to Keith Bigelow, general manager and senior vice president of the Salesforce Analytics Cloud. In order to provide capacity for Wave, he said, Salesforce has deployed thousands of servers and “many, many, many, many petabytes of storage” into its data centers — an order of magnitude more capacity than all the rest of

It’s hard to get an exact count of the current Salesforce footprint, but some old numbers put the scale of Wave into perspective. In 2011, the company was running about 3,000 servers globally, which was then about the size of a single Facebook Hadoop cluster. In 2013, a Salesforce engineer wrote a post at High Scalability citing “15,000+ hardware systems” and more than 22 petabytes of raw storage capacity.

Even if it’s still nowhere near the estimated million-plus servers operated by massive-scale operations such as Google and Microsoft (possibly even Facebook), Bigelow’s assertions about the scale of Wave suggest Salesforce understands the amount of capacity that’s required not just to serve lots of users, but to store, analyze and visualize their data, as well.

Can racks of cloud servers help save the world? Source: Microsoft

Servers, and lots of them, are a big part of what keeps major web services humming? Source: Microsoft


That’s a good thing, because the cloud part of Wave is what will ultimately make or break its success. Sure, [company][/company] users have long complained about that product’s weak analytics features, but there are now plenty of good, easy and relatively inexpensive ways to analyze that data via API connections to other analytics applications. Making Wave a reasonably priced and highly scalable general-purpose analytics application, however, is where Salesforce really stands to benefit from it financially.

Research firm IDC estimates business analytics to be a roughly $40 billion market, Bigelow said, and Salesforce expects to take a big piece of it. It might be easy enough to distinguish itself from the legacy vendors that still command billions of that revenue, but the trickier part will be fending off the rising field of next-generation vendors that are increasingly based in the cloud, as well.

[company]Tableau Software[/company] is the most well known and is growing fast (it has a cloud service as well as desktop and server editions, and is still looking to improve its user experience and expand its user base) but startups such as [company]ClearStory Data[/company] (which is built atop the very fast Apache Spark framework) show a lot of promise, as well. In fact, even [company]Microsoft[/company] is ramping up the Excel experience to include remarkably easier ways to analyze and visualize data.'s Wave on an iPhone.’s Wave on an iPhone.

From a product perspective, Wave looks about like what you’d expect from an analytics application built in 2014. It’s intuitive, it’s fast, and it looks (based on the demo I saw) easy enough to drill down into data points, join datasets (in fact, it will suggest fields that might make good join candidates) or switch from view to view. It has a mobile app clearly designed for mobile displays, meaning it shows as much information as possible while keeping clutter to a minimum.

This being Salesforce, Wave certainly connects to data from the company’s other services, but also includes connectors to data in other business applications such as SAP and Oracle. And not to worry, users can also upload their own data in spreadsheet form if they need to analyze something not generated via a connected application or database.

What will be really interesting is to see how Salesforce evolves Wave in the months and years to come — whether it starts working in more advanced machine learning and predictive analytics, or perhaps begins targeting even smaller businesses than it already does. Bigelow said to “stay tuned” on the innovation front, because the company plans to iterate very fast.

Salesforce already changed the course of the CRM market and now, he said, “We think there’s the same opportunity to hit the reset button on the analytics industry.”