Based on our record, IPFS seems to be a lot more popular than Apache Flink. While we know about 288 links to IPFS, we've tracked only 27 mentions of Apache Flink. 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.
When I click on https://synapsemedia.io/ I get redirected to a link like https://ipfs.io/ipns/synapsemedia.io (to use ipfs.io instead of my local node). Source: about 1 year ago
You may already be aware that the Interplanetary File System or IPFS is a distributed storage network where computers from all over the world form nodes to share data. Source: about 1 year ago
In case of you don't trust them, it gets harder. Especially if you need to have it hosted without any trace to yourself. I'd probably pay a service to store my data on ipfs. You can pay with crypto. But I'm this case there's the question, how will you be able to access it. My thought would be to have a [tails][tails] USB with the necessary software. Source: about 1 year ago
Https://ipfs.io is the only acceptable file host. Source: about 1 year ago
I never click GET button, don't even know what it does tbh XD Those four buttons are for choosing which IPFS gateway you want to use. By default I use ipfs.io, if ipfs.io is down then I click the Cloudflare one. General rule is that you pick one gateway if it does not work then another one and so on. Source: over 1 year 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 / 23 days 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 / 3 months ago
Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 4 months ago
Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
Due to the technology transformation we want to do recently, we started to investigate Apache Iceberg. In addition, the data processing engine we use in house is Apache Flink, so it's only fair to look for an experimental environment that integrates Flink and Iceberg. - Source: dev.to / 5 months ago
Dropbox - Online Sync and File Sharing
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
FileCoin - Filecoin is a data storage network and electronic currency based on Bitcoin.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Google Drive - Access and sync your files anywhere
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.