geometry-api-java
geomesa
geometry-api-java | geomesa | |
---|---|---|
2 | 3 | |
688 | 1,394 | |
0.4% | 1.1% | |
4.2 | 9.1 | |
about 1 month ago | 7 days ago | |
Java | Scala | |
Apache License 2.0 | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
geometry-api-java
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What should be my go-to programming language for this scenario?
I programmed with graphical interface in the past in Java, too, which is definitely one of the top choices for me cause it gives the code a lot of structure and makes it easier to maintain and on top of that there exists a lot of community run libraries that might serve my purpose, like this one. I mostly have experience in designing games (SuperMario, Space Invaders and similar) with Java.
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PostGIS – Spatial and Geographic Objects for PostgreSQL
It's good software (I've used it more than a decade), however I found GEOS to be a sticking point. When using it on very large polygons, e.g. 10k to 1 million vertices, memory leaks are not uncommon and performance drops off considerably. Debugging SQL -> C -> C++ is not fun and hacking C++ geometry code when it's not part of your normal work is nigh on impossible. I've found the ESRI geometry API for Java to be by far the best geometry API out there. Harder to use initially and obviously JVM specific but faster and more reliable. It's a very good fit for Hadoop / Spark or other JVM applications. Ignore the brand name, I'm not affiliated and it's FOSS with an Apache license.
https://github.com/Esri/geometry-api-java
geomesa
- GeoMesa
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Cool Dockerization Ideas
you could help dockerizing geomesa with/on Cassandra https://www.geomesa.org/ Currently its only dockerized with accumulo
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PostGIS – Spatial and Geographic Objects for PostgreSQL
If you really need to scale beyond what Postgres/PostGIS can handle, then you might want to check out GeoMesa[1], which is (very loosely) "PostGIS for HBase, Cassandra, or Google BigTable".
That being said, you may not need it, because Postgres/PostGIS can scale vertically to handle larger datasets than most people realize. I recommend loading your intended data (or your best simulation of it) into a Postgres instance running on one of the extremely large VMs available on your cloud provider, and running a load test with a distribution of the queries you'd expect. Assuming the deliberately over-provisioned instance is able to handle the queries, you can then run some experiments to "right-size" the instance to find the right balance of compute, memory, SSD, etc. If it can handle the queries but not at the QPS you need, then read replicas may also be a good solution.
[1] https://github.com/locationtech/geomesa
What are some alternatives?
open-data - Free football data from StatsBomb
docker-postgis - Docker image for PostGIS
plpgsql_check - plpgsql_check is a linter tool (does source code static analyze) for the PostgreSQL language plpgsql (the native language for PostgreSQL store procedures).
stud - Cartography 2019
solutions-geoevent-java - Custom processors, adapters and transports for geoevent server.
sample-data - Metrica Sports sample tracking and event data