Many web companies deal with enormous data sizes and request rates beyond the
capabilities of traditional database systems. This has led to the development
of modern Big Data Platforms (BDPs). BDPs handle large amounts of data and
activity through massively distributed infrastructures. To achieve performance
and availability at Internet scale, BDPs restrict querying capability, and
provide weaker consistency guarantees than traditional ACID transactions. The
reduced functionality as found in key-value stores is sufficient for many web applications.
An important requirement of many big data systems is an online view of the current status of the data and activity. Typical big data systems such as key-value stores only allow a key-based access. In order to enable more complex querying mechanisms, while satisfying necessary latencies materialized views are employed. The efficiency of the maintenance of these views is a key factor of the usability of the system. Expensive operations such as full table scans are impractical for small, frequent modifications on Internet-scale data sets. In this paper, we present an efficient implementation of materialized views in key-value stores that enables complex query processing and is tailored for efficient maintenance.