Super-Structured Data: Rethinking the Schema

• ontop

  1 611 9.6 Java

  Ontop is a platform to query relational databases as Virtual RDF Knowledge Graphs using SPARQL

  

> Ok, fine. But I'm not sure how this helps if you have six different systems with six different definitions of a customer, and more importantly, different relationships between customers and other objects like orders or transactions or locations or communications.

If you have this problem, consider giving RDF a look - you can fairly easily use RDF based technologies to map the data in these systems onto a common model, some examples of tools that may be useful here is https://www.w3.org/TR/r2rml/ and https://github.com/ontop/ontop - you can also use JSON-LD to convert most JSON data to RDF. For more info ask in https://gitter.im/linkeddata/chat

• awesome-semantic-web

  5 1,311 6.1

  A curated list of various semantic web and linked data resources.

  

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• zed

  13 1,305 9.5 Go

  A novel data lake based on super-structured data (by brimdata)

  

Cool, I didn't realize you used sqlite-utils for your performance demo!

It's not particularly designed for speed - it should be fast as far as Python code goes (I use some generator tricks to stream data and avoid having to load everything into memory at once) but I wouldn't expect "sqlite-utils insert" to win any performance competitions with tools written in other languages.

Those benchmarks against sqlite itself are definitely interesting. I'm looking forward to playing with the "native ZNG support for Python" mentioned on https://github.com/brimdata/zed/blob/main/docs/libraries/pyt... when that becomes available.

Suggest a related project