Materialize
Apache Flink
Apache Kafka
RisingWave
ClickHouse
OctoSQL
Amazon Kinesis
Timeplus
Apache Struts
Spring Framework
Grails
Spark Mail
Play Framework
Eclipse Jetty
Eclipse RAP
Vaadin Framework
MaterializeBased on our record, Materialize seems to be a lot more popular than Apache Struts. While we know about 74 links to Materialize, we've tracked only 2 mentions of Apache Struts. 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.
Did I miss in the article where OP reveals the magic database that actually does this? 3rd party solutions like https://readyset.io/ and https://materialize.com/ exist specifically because databases don’t actually have what we all want materialized views to be. - Source: Hacker News / about 1 year ago
This triggered some associations for me. Strongest was Cells[0], a library for Common Lisp CLOS. The earliest reference I can find is 2002[1], making it over 20 years old. Second is incremental view maintenance systems like Feldera[2] or Materialize[3]. These use sophisticated theories (z-sets and differential dataflow) to apply efficient updates over sets of data, which generalizes the case of single variables.... - Source: Hacker News / about 1 year ago
It's hard to write something that is both accessible and well-motivated. The best uses of category theory is when the morphisms are far more exotic than "regular functions". E.g. It would be nice to describe a circuit of live queries (like https://materialize.com/ stuff) with proper caching, joins, etc. Figuring this out is a bit of an open problem. Haskell's standard library's Monad and stuff are watered down to... - Source: Hacker News / almost 2 years ago
> [...] `https://materialize.com/` to solve their memory issues [...] Disclaimer: I work at Materialize Recently there have been major improvements in Materialize's memory usage as well as using disk to swap out some data. I find it pretty easy to hook up to Postgres/MySQL/Kafka instances: https://materialize.com/blog/materialize-emulator/. - Source: Hacker News / almost 2 years ago
I agree. So many disparate solutions. The streaming sql primitives are by themselves good enough (e.g. `tumble`, `hop` or `session` windows), but the infrastructural components are always rough in real life use cases. Crossing fingers for solutions like `https://github.com/feldera/feldera` to solve their memory issues, or `https://clickhouse.com/docs/en/materialized-view` to solve reliable streaming consumption.... - Source: Hacker News / almost 2 years ago
The Apache Struts website (https://struts.apache.org/) offers tutorials and other resources for learning about the Apache Struts framework. Source: over 3 years ago
3) Struts 2 - Also a popular java based framework. Backed by the Apache Foundation and built to easily integrate with Spring. This is the easiest choice when converting from a Struts 1 framework to a more modern and secure framework. - Source: dev.to / almost 5 years ago
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Grails - An Open Source, full stack, web application framework for the JVM
RisingWave - RisingWave is a stream processing platform that utilizes SQL to enhance data analysis, offering improved insights on real-time data.
Spark Mail - Spark helps you take your inbox under control. Instantly see what’s important and quickly clean up the rest. Spark for Teams allows you to create, discuss, and share email with your colleagues