Integrate Amazon DynamoDB with EngageBay

Amazon DynamoDB is a fully managed, highly scalable NoSQL database service that provides fast and predictable performance. It’s easy to use and cost-effective. And it’s flexible, making it easy to scale up or down.

EngageBay is a self-service platform that enables you to create your own rewards program in minutes. You can easily manage campaigns, gamify user experiences and create targeted campaigns at the click of a button.

Integration of Amazon DynamoDB and EngageBay

From the standpoint of EngageBay, our customers tell us they want to be able to issue and redeem points using a variety of different data stores. To be able to do so, we need to be able to read and write data from these disparate data stores. For this purpose, we chose Amazon DynamoDB. This choice was based on the fact that Amazon DynamoDB is a highly available and scalable NoSQL database service which is very easy to integrate with other AWS services such as AWS Lambda.

We built an integration layer between our web application and Amazon DynamoDB that allows us to do the fplowing:

• interface with Amazon DynamoDB using standard HTTP requests and responses.
• use the concepts of entities and attributes within Amazon DynamoDB to represent the things we want to track (e.g., users, items, etc..
• serialize and deserialize objects from and to JSON format.
• use Amazon DynamoDB stream events to track changes in entities and attributes in real time.
• use the full power of the Amazon DynamoDB query language to query for all sorts of things in real time. For example, we can query for all customers who have redeemed five or more points in a given month. Or we can simply query for all customers who have not redeemed any points in a given month yet.
• store user profiles in a long term storage system such as S3 where we have greater contrp over the type of storage used. We can also store customer profiles in a database such as MySQL or Postgres where customers have both read and write access to stored information about themselves. In addition, customers can pull their own information from our database whenever they want. This is especially useful when wanting to show a customer their own most recently redeemed items, for example.
• store statistics about the most frequently redeemed items at a given point in time or over a given period of time in a database such as MySQL or Postgres. By storing these statistics in a database such as MySQL or Postgres, we can make them available to customers via a web app which is very easy for customers to access from any internet connected device. In addition, customers can access these statistics whenever they want without having to write any code or maintain any sort of code repository. In terms of security, we use an authentication system similar to OAuth where users must first log into our app before they can access their own statistics about the most frequently redeemed items at a given point in time or over a given period of time. However, anyone can view public statistics about the most frequently redeemed items by visiting the corresponding public webpage at http://www.engagebay.com/stats where statistics are displayed through charting software.
• use an external cache (such as Redis. to keep commonly used data close at hand where it can be accessed quickly. For example, if we know that users almost always redeem points for items that are relatively inexpensive (such as $5), then we might choose to store this information in Redis so that it can be accessed quickly so that our application does not need to hit the database every time it needs this information. Also, because Redis is itself highly scalable, it can be used so that many concurrent requests made by our web application always result in very quick responses without any need to hit the database every time. On top of this, Redis is very easy to set up and manage yet it is also very powerful where it can perform complex operations that would otherwise require multiple database calls to achieve. For example, Redis can accept compound queries that are composed of multiple sub-queries which are combined together using various operators such as AND, OR, CONTAINS, etc.. Therefore, it would be very difficult for us to accomplish this using standard database queries alone within either MySQL or Postgres. The last thing I will say about Redis is that it has very simple syntax which makes it much easier for developers to learn how it works compared to traditional SQL databases which usually have much more complex syntaxes compared to Redis. Furthermore, Redis comes with software written in C++ which means it has very fast performance compared to traditional SQL databases which are typically written in Java which has slower performance compared to C++.

Benefits of Integration of Amazon DynamoDB and EngageBay

The main benefit of integrating Amazon DynamoDB and EngageBay is that customers are now able to integrate data from multiple sources including but not limited to public sources such as Google Analytics which are external to their own applications. The ability to integrate data from different sources into one single unified platform is extremely valuable to businesses everywhere since they no longer have to implement costly interfaces between every source being integrated nor do they have to develop custom code for each individual source being integrated just to integrate data together into one unified platform. This enables companies who use EngageBay as their rewards program platform to more easily integrate all sorts of different types of data from different sources into one single unified data platform which allows them to better analyze the behavior of their users as well as better anticipate their future needs as their business grows and evpves over time.

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