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  1. Stackups
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  5. Couchbase vs PostGIS

Couchbase vs PostGIS

OverviewDecisionsComparisonAlternatives

Overview

Couchbase
Couchbase
Stacks505
Followers606
Votes110
PostGIS
PostGIS
Stacks379
Followers377
Votes30
GitHub Stars2.0K
Forks407

Couchbase vs PostGIS: What are the differences?

Couchbase: Document-Oriented NoSQL Database. Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands; PostGIS: Open source spatial database. PostGIS is a spatial database extender for PostgreSQL object-relational database. It adds support for geographic objects allowing location queries to be run in SQL.

Couchbase can be classified as a tool in the "Databases" category, while PostGIS is grouped under "Database Tools".

Some of the features offered by Couchbase are:

  • JSON document database
  • N1QL (SQL-like query language)
  • Secondary Indexing

On the other hand, PostGIS provides the following key features:

  • Processing and analytic functions for both vector and raster data for splicing, dicing, morphing, reclassifying, and collecting/unioning with the power of SQL
  • raster map algebra for fine-grained raster processing
  • Spatial reprojection SQL callable functions for both vector and raster data

"Flexible data model, easy scalability, extremely fast" is the primary reason why developers consider Couchbase over the competitors, whereas "De facto GIS in SQL" was stated as the key factor in picking PostGIS.

PostGIS is an open source tool with 645 GitHub stars and 246 GitHub forks. Here's a link to PostGIS's open source repository on GitHub.

HotelTonight, Key Location, and Kalibrr are some of the popular companies that use PostGIS, whereas Couchbase is used by Geefu, Vestiaire Collective, and Hammerhead. PostGIS has a broader approval, being mentioned in 53 company stacks & 15 developers stacks; compared to Couchbase, which is listed in 45 company stacks and 21 developer stacks.

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Advice on Couchbase, PostGIS

Gabriel
Gabriel

CEO at Naologic

Jan 2, 2020

DecidedonCouchDBCouchDBCouchbaseCouchbaseMemcachedMemcached

We implemented our first large scale EPR application from naologic.com using CouchDB .

Very fast, replication works great, doesn't consume much RAM, queries are blazing fast but we found a problem: the queries were very hard to write, it took a long time to figure out the API, we had to go and write our own @nodejs library to make it work properly.

It lost most of its support. Since then, we migrated to Couchbase and the learning curve was steep but all worth it. Memcached indexing out of the box, full text search works great.

592k views592k
Comments
Mike
Mike

Mar 20, 2020

Needs advice

We Have thousands of .pdf docs generated from the same form but with lots of variability. We need to extract data from open text and more important - from tables inside the docs. The output of Couchbase/Mongo will be one row per document for backend processing. ADOBE renders the tables in an unusable form.

241k views241k
Comments

Detailed Comparison

Couchbase
Couchbase
PostGIS
PostGIS

Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.

PostGIS is a spatial database extender for PostgreSQL object-relational database. It adds support for geographic objects allowing location queries to be run in SQL.

JSON document database; N1QL (SQL-like query language); Secondary Indexing; Full-Text Indexing; Eventing/Triggers; Real-Time Analytics; Mobile Synchronization for offline support; Autonomous Operator for Kubernetes and OpenShift
Processing and analytic functions for both vector and raster data for splicing, dicing, morphing, reclassifying, and collecting/unioning with the power of SQL;raster map algebra for fine-grained raster processing;Spatial reprojection SQL callable functions for both vector and raster data;Support for importing / exporting ESRI shapefile vector data via both commandline and GUI packaged tools and support for more formats via other 3rd-party Open Source tools
Statistics
GitHub Stars
-
GitHub Stars
2.0K
GitHub Forks
-
GitHub Forks
407
Stacks
505
Stacks
379
Followers
606
Followers
377
Votes
110
Votes
30
Pros & Cons
Pros
  • 18
    Flexible data model, easy scalability, extremely fast
  • 18
    High performance
  • 9
    Mobile app support
  • 7
    You can query it with Ansi-92 SQL
  • 6
    All nodes can be read/write
Cons
  • 3
    Terrible query language
Pros
  • 25
    De facto GIS in SQL
  • 5
    Good Documentation
Integrations
Hadoop
Hadoop
Kafka
Kafka
Elasticsearch
Elasticsearch
Kubernetes
Kubernetes
Apache Spark
Apache Spark
PostgreSQL
PostgreSQL

What are some alternatives to Couchbase, PostGIS?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

dbForge Studio for MySQL

dbForge Studio for MySQL

It is the universal MySQL and MariaDB client for database management, administration and development. With the help of this intelligent MySQL client the work with data and code has become easier and more convenient. This tool provides utilities to compare, synchronize, and backup MySQL databases with scheduling, and gives possibility to analyze and report MySQL tables data.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

dbForge Studio for Oracle

dbForge Studio for Oracle

It is a powerful integrated development environment (IDE) which helps Oracle SQL developers to increase PL/SQL coding speed, provides versatile data editing tools for managing in-database and external data.

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