Based on our record, Apache Pig should be more popular than Dat. It has been mentiond 2 times since March 2021. 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.
Yes there are some really interesting projects, also in the ML replicability space. One really nice approach is the DAT project [1]. The protocol [2] looks pretty sensible and useful. Unfortunately, the tooling has been in such a state of permanent flux (i.e. Perpetual deprecation) that I've never bothered to invest much time. [1] https://datproject.org/ [1] https://datproject.org/. - Source: Hacker News / about 2 years ago
Pig, a platform/programming language for authoring parallelizable jobs. - Source: dev.to / over 1 year ago
In the early days of the Big Data era when K8s hasn't even been born yet, the common open source go-to solution was the Hadoop stack. We have written several old-fashioned Map-Reduce jobs, scripts using Pig until we came across Spark. Since then Spark has became one of the most popular data processing engines. It is very easy to start using Lighter on YARN deployments. Just run a docker with proper configuration... - Source: dev.to / over 2 years ago
Beaker browser - Beaker is a browser for IPFS and Dat.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
IPFS - IPFS is the permanent web. A new peer-to-peer hypermedia protocol.
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
Sia - Sia - Decentralized data storage
Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)