Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.
Based on our record, Redis seems to be a lot more popular than Apache Storm. While we know about 183 links to Redis, we've tracked only 11 mentions of Apache Storm. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The page 404s for me currently and it does not seem to be archived by the wayback machine either: https://web.archive.org/web/20240000000000*/https://redis.io/news/121. - Source: Hacker News / 25 days ago
Redis - real time data storage with different data structures in a cache. - Source: dev.to / 27 days ago
Redis.io no longer mentions open source. They have still not changed meta description on their page. It still says it is open source ^^ view-source:https://redis.io/. - Source: Hacker News / about 2 months ago
Follow the steps below to install Redis:. - Source: dev.to / 2 months ago
Redis: An open-source, in-memory data structure store supporting various data types. It offers persistence, replication, and clustering, making it ideal for more complex caching requirements and session storage. - Source: dev.to / 2 months ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 1 year ago
Storm, a system for real-time and stream processing. - Source: dev.to / over 1 year ago
Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 1 year ago
Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 2 years ago
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.