Adaptive Intelligence API

The API/BAAS Market is On Fire

By Jason Lobel • June 05, 2013

The market for API tools and backend-as-a-service (BaaS) infrastructure is on fire. Over $300 million of mergers and a capital raise were announced in just a two-week period in April, including:

  • 4/17: Intel acquiring Mashery, an API management tools vendor for $100 to $180 million
  • 4/22: CA acquiring Layer7, an API management tools vendor for $100 to $180 million
  • 4/23: Mulesoft acquiring ProgrammableWeb, the leading API media source at an undisclosed price
  • 4/24: 3Scale, an API management tools vendor, raising a $4.2 million Series A round
  • 4/29: Facebook acquiring Parse, a BaaS for mobile applications for $85 million

Why is this market so hot? A few core themes are driving demand for API/BaaS, such as:

  • Growth in I/P/SaaS: The proliferation in cloud-based vendors, most of which have APIs
  • Mobility: desire for single access point for data and messaging, location, and other mobile functionality for web, Android, iOS, Microsoft and other touchpoints
  • Data-driven applications: APIs allow for complex, intelligent applications (e.g., personalization) to be built, increasingly from dynamic, JavaScript-based single page applications 

While APIs expose a function (e.g., a Facebook “like”) or data (e.g., product information), BaaS platforms offer purpose-built functional and data API building blocks to solve problems for a particular niche (e.g., mobile apps, big data, etc). BaaS allows clients to build applications and use APIs without having to worry about setting up a database or configuring and scaling servers. 

For years, leaders such as Google, Facebook, Amazon and eBay, have made many services available to developers, customers and partners via APIs. Today, many startups are launching API-first strategies to maximize business development to gain traction faster and compete better from the start. Twilio and Braintree have demonstrated how an API-first design can disrupt multi-billion dollar industries quickly. Soon, there will be over 10,000 public and tens or hundreds of thousand of private APIs. This trend has sparked a crop of emerging players, like Runscope, that specialize in API products such as testing, task automation, security, and monitoring, among others. It will only be a matter of time before a Lumascape for the API market exists. Illustrated below is the trajectory of publicly listed APIs tracked by Programmable Web.

API Growth Chart

However, large non-technology enterprises, especially retailers, have been slow to adopt agile data strategies and create API infrastructure. These companies tend to suffer from inefficient waterfall development processes, highly customized, complex on-premise enterprise software and a reliance on third-party developers. Typically, if an application was built, a developer had to request help from protective database admins to learn how to access data from each system. This is inefficient and a problem that compounds when many applications are needed to serve a multi-channel consumer. A BaaS can reduce application development time anywhere from 30-60% by eliminating common backend development tasks.

Data APIs are valuable because they enable developers to learn and consume information easily to build customer experiences faster.  This is more important than ever with the shift to mobile and social causing content discovery to continuously change. Enterprises will learn how to be agile or they will fall behind. Businesses with multi-channel customer engagement, such as retailers, distributors and airlines find it incredibly challenging and costly to compete without services-based API infrastructure. We expect these challenges will only accelerate in the future Internet of Things whereby billions of machines (e.g., sensors, glasses, devices) will be connected. The modern day CMO will need a way to distribute content anywhere, access real-time data, programmatically trigger personalized customer engagement and find low-risk ways to test and build new consumer channels. 

Enterprises should consider building or licensing BaaS infrastructure to connect disparate systems into a single interface and enable data APIs that are secure, abstracted from complex backend systems, scalable to serve web applications, able to process big data. Legacy systems are not suitable and suffer from being complex to learn, risky to expose and costly or unable to scale. We believe large retailers like Wal-Mart and the Gap are taking steps in the right direction to tie operations and content for online and offline stores in the cloud. Wal-Mart announced they are building a common technology to “connect every product with every customer and let them decide how to shop.” Gap reportedly will spend around $5 million over two years to develop similar infrastructure. Many mid-to-large retailers will not have the human or capital resources to build API infrastructure to compete against Amazon and others in this hyper competitive, data-driven retail environment.  At SwiftIQ, we seek to fill this gap by empowering clients to create actionable experiences and insights to engage customers and operate smarter.  We do this by offering a BaaS for big data with purpose-built APIs for product, customer, orders, search, commerce and more.


In the last few years, hundreds of millions of venture capital has funded API-centric companies. We forecast this niche will continue to access capital and exit successfully to large strategic incumbents or via IPOs. We are in the early stages of golden era of open data and API/BaaS players. Leaders will emerge in a variety of niches beyond established API integration and management tools vendors. We believe the next phase will include big data and adaptive intelligence APIs that utilize modern, powerful databases and cost effective cloud networks. As Kin Lane identified, the future may likely result in companies building applications from virtualized API stacks to access core components on a low friction, pay-per-use basis from many best-of-breed vendors instead of investing millions in a large enterprise system.


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