PostgreSQL with PostGIS - best way for rapid development spatial-engaged services
April 02, 2021

PostgreSQL with PostGIS - best way for rapid development spatial-engaged services

Vladimir Salnikov | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with PostgreSQL

I've used PostgreSQL for managing the database for agriculture support system with elements of spatial analysis by PostGIS extension. This was an internal software (not intended for public markets), used by agronomists, management, and shareholders of agricultural holdings in South Russia, Volgograd region. The database includes records about crop rotations, vegetation indices, field observation data, weather data, etc. By this info, used in analytic to achieve better productivity and reduce expenses for common field works, used to grow bulk crops, such as wheat, corn, and sunflower.

Pros

  • Advanced spatial capabilities by using PostGIS extension
  • Very fast data processing and support of native ANSI SQL language syntax allows maintaining capability and scalability of database
  • Fast data aggregation, even by SQL or stored routines/functions
  • Well documented, free for use, great community. A lot of examples, and for this reason - lesser threshold for junior developers to start with

Cons

  • Clustering and distributed processing is difficult to use and maintain
  • Stability
  • Scalability
  • Well-documented
  • By using our product we managed to save over 8000 hectares of winter wheat at the years 2015-2020
  • MS SQL Server Express
The main reason for select PostgreSQL against MS SQL Server Express edition is the necessity to use open-source platform, without any issues for licensing, client licensing, etc. etc, which is usually follows developers and project managers when they start to use products and platform solutions from one well-known Redmond-based company :) Even the Express version of MS SQL is free for use, it has tons of restrictions and requires MS Server software, and client licensing to connect for. This is an expensive way, probably more stable and reliable than open-source but after risk assessment we selected PostgreSQL. And this was a 100% correct decision.

Do you think PostgreSQL delivers good value for the price?

Yes

Are you happy with PostgreSQL's feature set?

Yes

Did PostgreSQL live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of PostgreSQL go as expected?

Yes

Would you buy PostgreSQL again?

Yes

In my humble opinion, the best area to use PostgreSQL - is small and medium databases with several billion or tens of billions of records/entities with some spatial attributes analytics involved in the data processing pipeline, if needed. Using PostgreSQL with the conjunction of PostGIS extension and some other open-source software such as QuantumGIS, Leaflet, etc allows users rapidly create spatial data analytics software, maintain and modify it with few resources spend.

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