Hazelcast Powers Real-Time Infrastructure for E-commerce
Industry
E-commerce
Product
Hazelcast Platform Enterprise
Delivering e-commerce systems that provide competitive advantage is one of the toughest challenges facing retailers today. Flexibility and speed are the keys to building a world-beating e-commerce system. The ability to deliver a personalized shopping experience with relevant content at predictable sub-second latency is the difference between business success and failure. Customers will typically wait only 1 to 2 seconds for a page to load before moving on. Speedy response and high availability are absolute musts, and making sense of the huge volumes of data generated by customers is critical.
Some of the complex business requirements driving today’s e-commerce systems include:
- Generating personalized shopping experiences in microseconds using multiple data streams.
- Omni-channel systems that deliver a consistent shopping experience to the customer across mobile and web, and in store.
- Removal of data and system silos to present a single view of your data (warehousing, supply chain, social, customer).
- Flexible datastore that allows full scale updates to an entire product catalog in minutes rather than hours.
- The ability to meet peak demand workloads and then shrink systems at quieter periods to save compute costs.
- Dynamic pricing, comparing against competitors’ catalogs, and then adjusting pricing in real-time.
The business requirements listed above require systems and tools that are flexible and make use of virtual hardware platforms. Despite this, many business are attempting to deliver systems using technology that is decades old, resulting in a prohibitive total cost of ownership in terms of hardware, software, and time.
The Hazelcast Platform provides a unique set of characteristics that make it the perfect choice when building e-commerce systems. Increasingly businesses are turning to Hazelcast when their existing systems are unable to deliver on their service-level requirements. It’s not just older technologies such as Oracle databases that are struggling to cope; newer approaches using NoSQL databases are also failing to live up to promises. Hazelcast is the perfect complement to your existing system of record, enabling the performance and scalability that beats the competition.
| Why Most Datastores Fall Short | Why Hazelcast is Ideal |
|---|---|
On-demand scaling of most NoSQL and traditional relational databases is complex and expensive. Reacting to spikes in demand will often require manual intervention. | Adding more capacity to a Hazelcast cluster is simply a case of starting another node in response to increased demand, then removing the excess node at quieter times. Hazelcast takes care of the data distribution transparently without significant impact to transaction rates, all without operator intervention. |
Most other datastores manage the bulk of their data on disk, storing only a small amount of data in memory. This impacts transaction response times. | Hazelcast can store terabytes of data in memory to provide microsecond latencies while performing hundreds of thousands of transactions per second. |
Other datastores will often require additional software, often from other vendors, to provide a highly available, multi-data center solution. | Hazelcast includes all the features required to scale, not just locally but also across multiple data centers, while maintaining data coherence. |
Traditional databases impose strict schemas requiring upfront data modeling, costing time and money. | Hazelcast does not impose strict schemas on stored data. |
For performance reasons data must sometimes be stored in very large, document oriented, denormalized forms. e.g., an inventory item along with which stores carry it, how many are in each store, etc. Databases and NoSQL are very slow to read and process this type of data. | With in-situ processing (EntryProcessors) Hazelcast can process large documents and return just the data required, improving read performance. Updates to these documents can also be done in-situ, allowing just the change to be sent across the network. |
Customer Success Story
With $18.3 billion in annual online sales, this global provider of personal computers and electronics is one of the most visited e-commerce web sites in the world, second only to Amazon.com. Burst traffic during new product introductions is at an extreme scale, as are sales on Black Friday, Cyber Monday, and over the holidays. This unique combination of world-class brand experience and extreme burst performance scaling led this e-commerce giant to Hazelcast as the solution for achieving the best possible price performance for their e-commerce platform.
In the first phase, the customer scaled up to hundreds of nodes of open source Hazelcast with a commercial support agreement. Having launched, scaled, and operated this Hazelcast system for a year, the team then rolled out an even more significant phase two project. The Hazelcast deployment changed topology to a cluster of dedicated servers with distributed clients all connecting to the dedicated cluster, and the customer upgraded to Hazelcast Enterprise in order to take advantage of its off-Heap memory management feature, the High-Density Memory Store (HDMS). HDMS enabled them to scale up with a much smaller cluster on much larger machines, gaining them complete predictability over Garbage Collection pauses. The customer also moved from a proprietary cache abstraction layer to the Java standard, JCache. All of this enabled them to reduce cluster sizes from hundreds down to six servers with one node on each server and two copies of that in the same cluster. Each node will have 28GB cache space (likely to grow). So the total cache space will be 6 X 28GB = 168GB.
With this in place, the customer was able to meet their objectives of deploying an elastically scalable caching solution based on industry standards that could meet all of their needs while at the same time lowering both licensed software cost as well as hardware, development, operations, switching costs, and talent costs.