November 2018 Summaries

Redis, an in-memory database, offers versatility through its extensibility as a multi-model database, allowing it to be used for various use cases such as session management, caching, high-speed transactions, pub/sub, data streaming, analytics, and more. Its popularity stems from its wide range of programming languages support and client libraries. Redis can also be used as a relational database with the help of an ODBC connector, enabling applications like Tableau and Microsoft Excel to connect to it. The CData Software ODBC driver for Redis makes it even more accessible, allowing users to connect to data sources from various BI, analytics, and reporting tools stored in Redis. With the driver's installation and configuration, users can customize connection properties such as authentication schemes, table patterns, and logging settings to suit their needs.

Redis Enterprise has released a new version that marks a significant milestone in its journey towards zero latency, featuring improved graph database capabilities through RedisGraph and a new data structure called Streams. The new Streams feature provides an ordered collection of elements with unique sub-second timestamp-based identifiers, enabling fan-out scaling ability for pub/sub-like functionality. Additionally, Redis Enterprise collaborates with popular Redis clients Jedis and Redis-py to ensure support for all new features, including Streams and modules.

RedisGraph v1.0 has been released as a general availability module for Redis, offering graph database functionality. Unlike other graph databases, RedisGraph uses adjacency matrices and GraphBLAS to deliver fast and efficient graph operations, with initial benchmarks showing speeds of 6-600 times faster than existing graph databases. The new release is built on top of Redis's single-threaded process and leverages a threadpool for concurrent query execution, allowing for high throughput and low latency. Benchmark tests using the TigerGraph benchmark tool showed that RedisGraph outperformed other graph databases in both single request response time and parallel request throughput, with improvements ranging from 2-15,000 times faster than existing solutions. The release is part of a roadmap to further improve performance through profiling and adding new features.

Open source documentation` is a key concept that allows for modification and repackaging of product documentation by its community. This approach enables voluntary contributors to access the source code and contribute modifications, thereby improving the accuracy and timeliness of the documentation. By adopting an open source methodology, Redis aims to provide its customers with up-to-the-moment documentation that is curated by technical experts and the community itself, leading to a more collaborative and efficient documentation process.

We are excited to announce the preview of a jointly developed solution between Redis and Pivotal, which will deliver easy integration of Redis Enterprise as a native service on PKS. This solution gives developers instant access to a cloud-native data service that is portable, operationally simple and speeds up application development. Redis has grown in popularity due to its flexibility, speed and simplicity, making it the world's most loved database with over 1 billion pulls on Docker Hub. To manage multiple containers across machines, Kubernetes is used, while PKS handles operational burdens required for production-ready environments. The combination of Redis Enterprise and PKS eases common challenges with built-in high availability, monitoring and automated health checks. This solution will also support active-active replication using CRDTs for globally distributed applications.