Amazon DynamoDB vs PostGIS

Overview

Amazon DynamoDB

Stacks4.0K

Followers3.2K

Votes195

PostGIS

Stacks382

Followers377

Votes30

GitHub Stars2.0K

Forks407

Amazon DynamoDB vs PostGIS: What are the differences?

Data Structure: Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. It stores data in tables composed of items, which are collections of attributes. On the other hand, PostGIS is an open-source spatial database extender for PostgreSQL that adds support for geographic objects, allowing location queries and spatial analysis. It stores data in relational tables structured through schemas, with spatial data stored as geometries or geographies.
Query Language: Amazon DynamoDB uses a proprietary query language called AWS SDK, which allows developers to interact with the database using built-in commands. In contrast, PostGIS uses SQL (Structured Query Language) to query and manipulate spatial data, making it more familiar to those who are already proficient in SQL.
Geospatial Capabilities: PostGIS is specifically designed to handle geospatial data, providing functions and operators for geometry and geography types. This allows for advanced spatial queries, analysis, and visualization. DynamoDB, on the other hand, does not have built-in support for geospatial data, requiring developers to implement custom solutions or integrate with third-party tools for such functionality.
Scalability: Amazon DynamoDB is a fully managed service that automatically scales to accommodate growing workloads and storage needs. It offers seamless scalability without requiring manual intervention. PostGIS, being an extension of PostgreSQL, inherits its scalability features but may require more manual configuration and optimization for handling large spatial datasets efficiently.
Pricing Model: The pricing model for Amazon DynamoDB is based on provisioned throughput capacity, storage consumption, and data transfer. Users pay for the resources they provision, regardless of actual usage. PostGIS, being an open-source extension, is typically included as part of the PostgreSQL database deployment, with pricing based on the hosting provider or enterprise support options chosen.
Data Consistency: Amazon DynamoDB offers eventual consistency by default, providing highly available and scalable performance. Developers can choose strong consistency for specific read operations, ensuring immediate data consistency. PostGIS, being an extension of PostgreSQL, follows the ACID (Atomicity, Consistency, Isolation, Durability) principles, providing strong consistency for all operations within the database.

In Summary, Amazon DynamoDB and PostGIS differ in terms of data structure, query language, geospatial capabilities, scalability, pricing model, and data consistency.

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Advice on Amazon DynamoDB, PostGIS

Doru

Solution Architect

Jun 9, 2019

Reviewon

Amazon DynamoDB

I use Amazon DynamoDB because it integrates seamlessly with other AWS SaaS solutions and if cost is the primary concern early on, then this will be a better choice when compared to AWS RDS or any other solution that requires the creation of a HA cluster of IaaS components that will cost money just for being there, the costs not being influenced primarily by usage.

1.44k views1.44k

Comments

akash

Aug 27, 2020

Needs adviceon

Cloud Firestore

Firebase Realtime Database

Amazon DynamoDB

We are building a social media app, where users will post images, like their post, and make friends based on their interest. We are currently using Cloud Firestore and Firebase Realtime Database. We are looking for another database like Amazon DynamoDB; how much this decision can be efficient in terms of pricing and overhead?

199k views199k

Comments

Detailed Comparison

Amazon DynamoDB	PostGIS
With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.	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.
Automated Storage Scaling – There is no limit to the amount of data you can store in a DynamoDB table, and the service automatically allocates more storage, as you store more data using the DynamoDB write APIs;Provisioned Throughput – When creating a table, simply specify how much request capacity you require. DynamoDB allocates dedicated resources to your table to meet your performance requirements, and automatically partitions data over a sufficient number of servers to meet your request capacity;Fully Distributed, Shared Nothing Architecture	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 4.0K	Stacks 382
Followers 3.2K	Followers 377
Votes 195	Votes 30
Pros & Cons
Pros 62 Predictable performance and cost 56 Scalable 35 Native JSON Support 21 AWS Free Tier 7 Fast Cons 4 Only sequential access for paginate data 1 Scaling 1 Document Limit Size	Pros 25 De facto GIS in SQL 5 Good Documentation
Integrations
Amazon RDS for PostgreSQL PostgreSQL MySQL SQLite Azure Database for MySQL	PostgreSQL

What are some alternatives to Amazon DynamoDB, PostGIS?

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.

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.

dbForge Studio for SQL Server

It is a powerful IDE for SQL Server management, administration, development, data reporting and analysis. The tool will help SQL developers to manage databases, version-control database changes in popular source control systems, speed up routine tasks, as well, as to make complex database changes.

Azure Cosmos DB

Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.

Cloud Firestore

Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.

Liquibase

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Sequel Pro

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DBeaver

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dbForge SQL Complete

It is an IntelliSense add-in for SQL Server Management Studio, designed to provide the fastest T-SQL query typing ever possible.

Related Comparisons

Amazon DynamoDB vs PostGIS: What are the differences?

Data Structure: Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. It stores data in tables composed of items, which are collections of attributes. On the other hand, PostGIS is an open-source spatial database extender for PostgreSQL that adds support for geographic objects, allowing location queries and spatial analysis. It stores data in relational tables structured through schemas, with spatial data stored as geometries or geographies.
Query Language: Amazon DynamoDB uses a proprietary query language called AWS SDK, which allows developers to interact with the database using built-in commands. In contrast, PostGIS uses SQL (Structured Query Language) to query and manipulate spatial data, making it more familiar to those who are already proficient in SQL.
Geospatial Capabilities: PostGIS is specifically designed to handle geospatial data, providing functions and operators for geometry and geography types. This allows for advanced spatial queries, analysis, and visualization. DynamoDB, on the other hand, does not have built-in support for geospatial data, requiring developers to implement custom solutions or integrate with third-party tools for such functionality.
Scalability: Amazon DynamoDB is a fully managed service that automatically scales to accommodate growing workloads and storage needs. It offers seamless scalability without requiring manual intervention. PostGIS, being an extension of PostgreSQL, inherits its scalability features but may require more manual configuration and optimization for handling large spatial datasets efficiently.
Pricing Model: The pricing model for Amazon DynamoDB is based on provisioned throughput capacity, storage consumption, and data transfer. Users pay for the resources they provision, regardless of actual usage. PostGIS, being an open-source extension, is typically included as part of the PostgreSQL database deployment, with pricing based on the hosting provider or enterprise support options chosen.
Data Consistency: Amazon DynamoDB offers eventual consistency by default, providing highly available and scalable performance. Developers can choose strong consistency for specific read operations, ensuring immediate data consistency. PostGIS, being an extension of PostgreSQL, follows the ACID (Atomicity, Consistency, Isolation, Durability) principles, providing strong consistency for all operations within the database.

In Summary, Amazon DynamoDB and PostGIS differ in terms of data structure, query language, geospatial capabilities, scalability, pricing model, and data consistency.

Amazon DynamoDB vs PostGIS

Overview