We are mixing it up on you again, no Outlaw this week, but we can offer you some talk of exotic databases. Also, Joe pronounces everything correctly and Allen leaves you with a riddle.
The full show notes are available on the website at https://www.codingblocks.net/episode229
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Multivalue DBMS
- Popular: 86. Adabas, 87. UniData/UniVerse, 147. JBase
- Similar to RDBMS - store data in tables
- Store multiple values to a particular record's attribute
- Some RDBMS's can do this as well, BUT it's typically an exception to the rule when you'd store an array on an attribute
- In a MultiValue DBMS - that's how you SHOULD do it
- Part of the reason it's done this way is these database systems are not optimized for JOINS
- Looked at the Adabas and UniData sites - the primary selling points seem to be rapid application development / ease of learning and getting up to speed as well as data modeling that closely mirrors your application data structures
- I BELIEVE it's a schema on write (docs.rocketsoftware.com)
- Supposed to be very performant as you access the data the way your application expects it
- Per the docs, it's easy to maintain (Wikipedia)
Spatial DBMS
- Popular: 29. PostGIS, 59. Aerospike, 136. SpatiaLite
- Provides the ability to efficiently store, modify, and query spatial data - data that appears in a geometrical space (maps, polygons, etc)
- Generally have custom data types for storing the spatial data
- Indices that allow for quick retrieval of spatial data about other spatial data
- Also allow for performing spatial-specific operations on data, such as computing distances, merging or intersecting objects or even calculating areas
- Geospatial data is a subset of spatial data - they represent places / spatial data on the Earth's surface
- Spatio-temporal data is another variation - spatial data combined with timestamps