January 2022 Summaries

Redis v7.0 has been released as the first release candidate (RC1), marking a significant milestone in the project's development. This major release introduces new features such as Functions, ACL v2, sharded Pub/Sub, and more, while also focusing on improving and optimizing existing parts of Redis. The new version aims to deliver more raw power at better resource utilization, making it faster, more stable, and more economical. Redis Functions are a key addition, allowing for the execution of user logic on the server-side, providing an effective way to compose server-side workflows from core Redis operations and control structures. This feature enables the decoupling of application code from function implementation, promoting reusability, maintainability, and scalability.

You can run a shell command in Jupyter Notebook or Google Colab with IPython by prefixing it with the ! character or % to use magic commands. A list of useful magic commands for data scientists is described in Top 8 magic commands in Jupyter Notebook. You can install Redis and its Python client using the `!curl` and `%pip install redis` commands, respectively. To start the Redis server, run the `./redis-stack-server-6.2.6-v7/bin/redis-stack-server --daemonize yes` command. To verify that Redis is running, create a connection to it with the Python client and ping the server using the `client.ping()` method. You can then read and write data to Redis using its command functions such as `set`, `get`.

The benefits of application caching are speed and efficiency in accessing data, but maintaining cache consistency is a significant challenge due to three main pitfalls: when changes to the primary database aren't reflected in the cache, there's a delay in updating cached results, and inconsistency across cached nodes. Cache inconsistency can have severe consequences, such as damaging customer trust and reputation, and even legal jeopardy. Fortunately, solutions like cache invalidation, write-through caching, write-behind caching, and Redis Enterprise's active-active geo-duplication can address these challenges and ensure reliable delivery of consistency in enterprise-level database caching.

The latest release of redis-py, version 4.1.0, brings significant improvements to the Python support for Redis, including complete command support in Redis 6.2, SSL support for Sentinel connections, and improved developer experience. The new release adds over 30 commands, including GETEX, CLIENT INFO AND KILL, STORING and RETRIEVING JSON, FETCHING ALL KEYS NAMED “hello” from the JSON document, and integrating redis-cluster support with two easy ways to connect. Additionally, redis-py 4.1.0 supports RedisJSON, RediSearch, RedisTimeSeries, RedisGraph, and RedisBloom, making it easier to store and manipulate JSON data in Redis, as well as combining these features for advanced capabilities. The library also continues to evolve with support for Redis modules, cluster connections via SSL, and plans for future additions such as RedisAI and RESP3 functions.

GreenEarth`, an innovative application created by Rajesh Ramamurthy, utilizes `Redis` to reduce waste and promote a greener planet. The platform connects environmentally conscious people with projects that utilize household items, allowing users to repurpose common trash into useful items or creative art projects. With `Redis` enabling fast data processing, the application's components become more interconnected, providing an efficient user experience. By harnessing the power of `Redis`, GreenEarth aims to make a positive impact on climate change and encourage people to adopt a greener way of living.

A well-optimized gaming database is crucial for maximizing player engagement by providing seamless experiences in features such as leaderboards, game inventories, personalization, and smart matchmaking. Real-time data processing removes lags and provides instantaneous responses, eliminating the toxic effects of poor performance that can lead to a drop in daily active users, bad publicity, and an eroding brand reputation. A strong online community is also fostered through maximizing engagement, which hinges on fast, consistent, and accurate matchmaking processes that meet industry standards for responsiveness and consistency. In inventories, databases must process millions of queries at lightning speed with impeccable consistency to provide players seamless access without lags or delays. Personalization is a powerful component of gaming that creates a more immersive experience by blending players' tastes, preferences, and styles into the playing experience, while leaderboards require complex architectures of services and technologies to detect cheating patterns and process millions of queries simultaneously. Ultimately, real-time data processing requires a real-time database that meets technical requirements for supply all game features with real-time data to maximize player engagement and meet industry standards for responsiveness.

The Database-as-a-Service (DBaaS) model provides a hosted or managed cloud service that allows users to access database services without managing software or infrastructure, freeing up IT resources for more strategic tasks. It offers various features such as monitoring, alerts and notifications, round-the-clock support, geo-replication for availability and backups, and automated scaling to meet workload changes. DBaaS provides business agility, security, high availability, and cost-effectiveness, making it an attractive solution for modern applications that require rapid provisioning, scalability, and performance. With the growth of cloud computing and the increasing demand for low-latency queries, selecting the right DBaaS provider is critical to the success of any cloud-based database management system.

The database market has undergone significant transformations over the past two years, with businesses rapidly adopting cloud initiatives to modernize their existing apps and launch new greenfield apps. Gartner reports that cloud database management system revenue will account for 50% of the total DBMS market revenue by 2022, up from an earlier forecasted date. Redis has been recognized as a Challenger in the Magic Quadrant for Cloud Database Management Systems for the second consecutive year, reflecting its "One Redis" vision to deliver a platform that provides speed, flexibility, and scalability across cloud providers. Gartner's evaluation highlights Redis Enterprise Cloud's capabilities in addressing various operational use cases, including traditional transactions, augmented transactions processing, stream/event processing, and operation intelligence use cases. The company's commitment to delivering a robust caching solution, ease of use, and simplicity has earned it over 4.6 out of 5 ratings and 100% "would recommend" on Gartner Peer Insights, with customers praising its performance, reliability, security, and scalability.

The Helplanet application, developed by Bryon Rosas Salguero, aims to make reporting community issues easier and more efficient. The app uses Redis, a real-time data transmission platform, to enable users to report social issues such as hazardous waste or environmental concerns instantly from their mobile devices. Once reported, the incidents are stored in a database and sent to organizations, which can view them on their dashboard, filter by location, and even contact the reporter directly. The app's architecture relies heavily on Redis to ensure seamless data transmission and hyper-efficient processing of reports, allowing for real-time updates and efficient management of community issues.

We have reached the final post in our “Redis in 90 seconds” series, which aims to briefly highlight a few lesser-known topics about Redis and provide guidance on lowering costs with Redis Enterprise. Despite other Redis providers offering similar features at higher costs, Redis Enterprise starts at just $7/mo and stays as low as $0 for the first six months when using credits, making it an attractive option for small and medium-sized businesses. With its optimized performance and cost savings capabilities, Redis Enterprise can help users achieve up to 80% in savings versus other cloud providers by storing data on Flash and achieving sub-millisecond latencies while keeping costs minimal.

The digital economy has undergone significant changes, with consumer habits shifting towards digital interactions, and businesses needing to transform their approach to stay competitive. Redis is reinventing how companies approach data, challenging traditional assumptions about separate data platforms and siloed infrastructure, by providing a unified real-time source that increases agility and accelerates time to market, while also cutting costs and reducing technical debt.