Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

PostGIS

Stacks381

Followers377

Votes30

GitHub Stars2.0K

Forks407

Cassandra vs PostGIS: What are the differences?

# Introduction

1. **Data Model:** Cassandra is a NoSQL database that uses a wide-column store data model, allowing for flexible schema and horizontal scaling. PostGIS, on the other hand, is an extension of PostgreSQL that adds support for geographic objects, allowing for spatial data storage and queries.
2. **Primary Use Case:** Cassandra is commonly used for high-velocity, high-volume distributed data where scalability and fault tolerance are crucial. PostGIS, on the other hand, is primarily used for geographical information systems (GIS), allowing for spatial analysis and location-based queries.
3. **Data Querying:** Cassandra uses CQL (Cassandra Query Language) for querying data, which is based on SQL but has some differences. PostGIS uses SQL for querying but also provides spatial functions and operators for spatial queries.
4. **Indexing:** Cassandra relies on distributed indexes to quickly look up data in a distributed environment, while PostGIS utilizes spatial indexes for efficient spatial data retrieval, making it suitable for spatial queries on large datasets.
5. **Consistency:** Cassandra offers tunable consistency levels, allowing trade-offs between consistency, availability, and partition tolerance. PostGIS, being an extension of PostgreSQL, follows ACID properties and offers strong consistency guarantees for spatial data operations.
6. **Scalability:** Cassandra is designed for horizontal scalability, allowing for linear scaling by adding more nodes to the cluster. In contrast, while PostgreSQL can scale vertically by adding more resources to a single server, PostGIS does not inherently provide horizontal scalability features for spatial data storage and queries.

In Summary, the key differences between Cassandra and PostGIS lie in their data models, primary use cases, data querying methods, indexing strategies, consistency levels, and scalability options.

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Advice on Cassandra, PostGIS

Vinay

Head of Engineering

Sep 19, 2019

Needs advice

The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.

The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.

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Comments

Detailed Comparison

Cassandra	PostGIS
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.	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.
-	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 9.5K	GitHub Stars 2.0K
GitHub Forks 3.8K	GitHub Forks 407
Stacks 3.6K	Stacks 381
Followers 3.5K	Followers 377
Votes 507	Votes 30
Pros & Cons
Pros 119 Distributed 98 High performance 81 High availability 74 Easy scalability 53 Replication Cons 3 Reliability of replication 1 Updates 1 Size	Pros 25 De facto GIS in SQL 5 Good Documentation
Integrations
No integrations available	PostgreSQL

What are some alternatives to Cassandra, PostGIS?

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

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 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

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

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.

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

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

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.

dbForge Studio for PostgreSQL

It is a GUI tool for database development and management. The IDE for PostgreSQL allows users to create, develop, and execute queries, edit and adjust the code to their requirements in a convenient and user-friendly interface.