October 2018 Summaries

Redis introduced version 4.0 with an API for extending its capabilities via new commands and data types. RediSearch uses this feature to enable full-text search of data stored in Redis. One challenge faced by search engines is deleting and updating documents, which RediSearch tackles using a Garbage Collection (GC) mechanism. The previous approach was slow as it required scanning the entire index and acquiring a global lock. To address this issue, RediSearch developed a new GC approach that leverages Linux fork processes to minimize lock acquisition time and improve performance. This new approach is available in version 1.4.1 but is currently experimental and not recommended for production use. Future enhancements may include using heuristics to prioritize garbage collection.

The Internet of Things (IoT) presents a unique challenge for databases due to its increasing data volume and velocity, requiring near-instant response times. To address this, data processing and analysis must be handled at the network edge, close to IoT devices. Fog computing is emerging as a solution that brings cloud principles to the edge, allowing complex IoT use cases to operate in tandem with cloud environments. RedisEdge, a multi-model database, delivers fast performance for handling large and high-velocity data from potentially thousands of sensors, cameras, and other devices at the IoT edge. Microsoft Azure IoT Edge is purpose-built to support these needs, integrating RedisEdge into its runtime environment for improved performance.

The latest release of Redis 5.0 introduces a new data structure called Streams, which allows storing multiple fields and string values with an automatic time-based sequence at a single key, resembling lists, hashes, sorted sets, and pub/sub patterns. This enables real-time reactions to the stream through consumer groups that allow various clients to consume a stream with their own position, making it suitable for tasks like event sourcing or unified log architecture. The release also includes new commands for sorting sets, such as removing the highest- or lowest-scoring member, as well as refinements to existing internals and a new LOLWUT command for testing purposes.

The partnership between Redis and Red Hat aims to help organizations rapidly develop and deploy modern cloud-native applications by leveraging the power of Kubernetes and Red Hat OpenShift Container Platform, which provides a powerful auto-scaling multi and hybrid cloud application platform for organizations. The joint solution simplifies the creation and management of highly available Redis Enterprise on the OpenShift Container Platform with built-in support for Redis Enterprise Operator for Kubernetes. This collaboration demonstrates a trend in the industry where enterprises are adopting microservice strategies to meet the pressure to develop and deploy applications quickly and securely, and both Redis and Red Hat share a common vision around their open source ecosystem. The partnership allows organizations to take advantage of the best open source platforms without taking on the risk of deploying unsupported technologies for mission-critical applications.

The text discusses how Redis Enterprise, an active-active database ideal for geo-distributed apps, can be set up using Docker. It provides a step-by-step guide on creating a CRDT-based Redis Enterprise database on a 3-node cluster through the command line. Additionally, it covers splitting and restoring networks to simulate network partitioning between replicas, as well as stopping all nodes of Redis Enterprise when testing is complete. The text also mentions that Redis Enterprise is available on Docker Hub as redis/redis and provides detailed instructions for setting up the database in the documentation page and docker hub itself.