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InfluxDB
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.
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We have used https://almond.sh/ to create a Spark SQL interpreter using Jupyter Notebooks - plus a whole lot more which you can see here: https://arc.tripl.ai/tutorial
After seeing many companies writing ETL using code we decided it was too hard to manage at scale so provided this abstraction layer - which is heavily centered around expressing business logic in SQL - to standardise development (JupyterLab) and allow rapid deployments.
The Github support for notebooks is so nice (was linked from the example pic caption: https://github.com/wangfenjin/xeus-tidb/blob/develop/example...)
but we offer full support to SOCI meaning if these folks: https://github.com/SOCI/soci support it and the dependencies exist and work for 32bit, than yes.
Jupyter would be even better if it supported the seamless combination of Python and SQL code cells.
My notebook code typically involves a data prep stage with querying a SQL database, then downloading into Python for more complex analysis, ML modelling, integration with external data sources, etc. So the notebook has a Python kernel with SQL usually as embedded """-quoted strings.
Does anyone have a solution to treating selected code cells as SQL - with SQL highlighting and tooltips - exposed as string variables to the Python code?
Sparkmagic [1] does part of this for Python/SQL/Spark interoperability, but as far as I recall, doesn't support SQL syntax highlighting.
[1] https://github.com/jupyter-incubator/sparkmagic
there have been some efforts in the past to do that: https://github.com/minrk/allthekernels