Deliver the shopping experience consumers demand.

Customers shopping online expect the highest level of performance on any device, anywhere. Increases in latency have substantial impacts on revenue. Amazon is well known for publishing that 100 milliseconds of latency costs them 1% of sales. What might start as abandoned carts can rapidly lead to abandoned loyalty.

Riak provides the high-availability, low-latency architecture needed to deliver an “always-on” shopping experience. Riak KV is a distributed NoSQL key-value database. Riak TS is specifically optimized for time series data. Whether you are serving up ads or a huge product catalog, Riak is ideal for storing things like content, user, and session data.

Riak’s masterless architecture provides high read and write availability, fault tolerance, and the ability to scale easily using commodity hardware.

Basho Customers


betzold logo






Riak for Retail and eCommerce

  • “Always-on” Shopping Experience — For retailers, failure to accept changes to a shopping cart, or serve product information quickly, has a direct and negative impact on revenue. Riak ensures retail infrastructure is resilient and fault tolerant, even in the event of network partition or hardware failures. Data is replicated automatically within the cluster, so if nodes go down the system can continue to respond to read and write requests.
  • Flexible Scale for Peak Seasons and Events — During major holidays and other peak load periods, many retailers have to quickly and significantly increase their database capacity. With Riak, new nodes can be quickly and easily added to the cluster with no sharding. Also, as nodes are added, Riak yields a near-linear increase in performance and throughput.
  • Manage Product Catalogs — Online retailing requires that product images, descriptions, product ratings, and reviews are served quickly. In order to provide a fast and available experience to end users, Riak KV is designed to serve predictable, low-latency requests and is accessible via HTTP API, protocol buffers, or Riak’s many client libraries.
  • Optimize Customer Analytics — A successful online shopping experience heavily relies on time-stamped data. Price comparisons, product recommendations, and recently viewed products are all examples of customer analysis based on time series data. Riak TS is optimized for fast reads and writes of time series data so you can dynamically customize your customer’s experience based on their prior searches, pageviews, wish-list additions, written reviews, and purchases. Riak TS also integrates with Apache Spark for integrated in-memory analytics.
  • Scale Chat Services — Customers expect to reach you online. This makes chat a crucial component of any retail customer support strategy. To enable chat services at scale requires very fast reads and writes. Riak’s key/value design makes it ideal for supporting chat features, and for storing and serving social content.
  • Low-latent Global Access — Online and mobile retail customers shop from anywhere around the globe. Riak Enterprise with Multi-cluster Replication automatically syncs data across clusters, enabling you to serve data to your customers from whichever cluster is the closest and fastest. Customers get a fast and consistent shopping experience.

Customer Testimonials


Best Buy builds for speed with Riak KV Enterprise.

Best Buy, the 12th largest retailer in the United States, selected Riak KV Enterprise as an integral part of its transformative push to re-platform its eCommerce system. Riak KV Enterprise with Multi-cluster Replication ensures product images, descriptions, product ratings, and reviews for are served up fast.

videos  Watch the Video


Ideel uses Riak KV to better cater to customers.

Ideel, a flash shopping site, chose Basho Riak KV to power its online event based shopping experience. In addition, Riak is used for AB and multivariate testing to help determine user preferences for new features on the site. Plus, Ideel uses Riak to dynamically serve user-specific favorite products in a grid page.

   Read the Case Study