-
-
-
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.
-
We're using on the French national access point to transportation data (http://transport.data.gouv.fr/?locale=en, source code at https://github.com/etalab/transport-site) and we're not going to switch to another stack ^_^.
Plenty of use-cases are made easy by the stack, from regular web work, API (https://transport.data.gouv.fr/swaggerui) to proxying (https://github.com/etalab/transport-site/tree/master/apps/un...) to real-time maps (https://transport.data.gouv.fr/explore), clustered maps (https://transport.data.gouv.fr/explore/gtfs-stops), XML queries building (https://transport.data.gouv.fr/tools/siri-querier?endpoint_u...)...
The maintenance story is very good too.
With ML being added (Nx/Axon etc), and mobile apps being in the works (LiveViewNative), it has become my everyday language & stack.
One example is HTTP libraries.
For instance, take Mint (https://github.com/elixir-mint/mint):
> Mint is different from most Erlang and Elixir HTTP clients because it provides a process-less architecture.
Mint is a low-level library which doesn't make attempt to manage processes (including HTTP pooling).
In contrast, Finch (which builds on top of Mint) includes pool management:
https://github.com/elixir-mint/mint#connection-management-an...
It can take someone a bit off guard when they realise that the library they use provide a "default pool" they were not aware of, and that it can become a bottleneck etc.