Also if you are interested in what trans compiled code looks like, head to this site that will transcompile anything given to it. https://babeljs.io/. - Source: dev.to / 12 days ago

Some of the most popular JavaScript linting tools are ESLint, JSHint, JSLint and JSCS. We're going to be using ESLint. It’s very flexible, easy to use and has the best ES6 support, which will be helpful if we introduce more modern JavaScript (that will be transpiled for older browsers using https://babeljs.io/). All rules for ESLint can be found here: https://eslint.org/docs/rules/. - Source: dev.to / 4 months ago

This simply extends the existing build process that many front-end frameworks have. After Babel's done with its transpilation, it merely executes code to compile your initial screen into static HTML and CSS. This isn't entirely dissimilar from how SSR hydrates your initial screen, but it's done at compile-time, not at request time. - Source: dev.to / 4 months ago

First, we switched the default compiler for new projects from Babel to SWC (Speedy Web Compiler). SWC is dramatically faster than Babel and requires zero configuration. We’ll continue to support Babel in any project currently using it. - Source: dev.to / 5 months ago

Nuxt.js is an open-source JavaScript framework built on Vue.js, Node.js, Vite, and Babel.js used for creating fast, cutting-edge applications. Nuxt.js possesses similar features to Next.js, with the major difference being the web framework it is compatible with. Next.js is a React framework whereas Nuxt.js is a Vue framework. - Source: dev.to / 7 months ago

Restate is built as a sharded replicated state machine similar to how TiKV (https://tikv.org/), Kudu (https://kudu.apache.org/kudu.pdf) or CockroachDB (https://github.com/cockroachdb/cockroach) since it makes it possible to tune the system more easily for different deployment scenarios (on-prem, cloud, cost-effective blob storage). Moreover, it allows for some other cool things like seamlessly moving from one log... - Source: Hacker News / 16 days ago

I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / about 1 month ago

You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / about 2 months ago

Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 3 months ago

Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 5 months ago