Apache Storm might be a bit more popular than Aerospike. We know about 11 links to it since March 2021 and only 8 links to Aerospike. 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.
Aerospike for LINQPad 7 is a data context dynamic driver for interactively querying and updating an Aerospike database using “LINQPad”. The driver is free. For more information go to this blog post. You can directly download the driver from the LINQPad NuGet manager. Source: about 1 year ago
Aerospike is a real-time cloud structured platform with good performance capabilities. This IMDB platform allows enterprises to perform their operations in real time through the hybrid memory and parallelism model. - Source: dev.to / over 1 year ago
Block storage stores a sequence of bytes in a fixed size block (page) on a storage device. Each block has a unique hash that references the address location of the specified block. Unlike a filesystem, block storage doesn't have the associated metadata such as format-type, owner, date, etc. Also, block storage doesn’t use the conventional storage paths to access data like a filesystem file. This reduction in... - Source: dev.to / over 1 year ago
This example shows how the Aerospike database can be easily and scalably used to store industrial time series data made available by the MQTT ecosystem. Aerospike plus its Community Time Series Client streamlines the storage and retrieval of the data, supporting the ability to both write and read millions of data points per second if required. - Source: dev.to / over 1 year ago
Real-time large-scale JSON applications need reliably fast access to data, high ingest rates, powerful queries, rich document functionality, scalability with no practical limit, always-on operation, and integration with streaming and analytical platforms. They need all this at low cost. The Aerospike Real-time Data Platform provides all this functionality, making it a good choice for building such applications.... - Source: dev.to / over 1 year 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lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem.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
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
memcached - High-performance, distributed memory object caching system
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.