Atlas-DB vs PostGIS

Overview

PostGIS

Stacks381

Followers377

Votes30

GitHub Stars2.0K

Forks407

Atlas-DB

Stacks6

Followers77

Votes0

GitHub Stars3.5K

Forks324

Atlas-DB vs PostGIS: What are the differences?

Introduction:

Atlas-DB and PostGIS are two popular databases used for spatial data management. While they both serve a similar purpose, there are key differences between them that differentiate their functionalities and use cases.

Data Model: Atlas-DB is a distributed key-value store with multi-dimensional indexing capabilities, optimized for storing and querying spatial and non-spatial data efficiently. On the other hand, PostGIS is an extension of PostgreSQL, adding support for geographic objects, spatial indexing, and spatial functions within a relational database model.
Scalability: Atlas-DB is designed for horizontal scalability, making it well-suited for large-scale distributed systems where data is spread across multiple nodes for high availability and performance. In contrast, PostGIS is more limited in scalability as it relies on a single relational database instance, which can be a bottleneck for high-traffic applications.
Geospatial Functionality: PostGIS offers a wide range of geospatial functions and capabilities, allowing users to perform complex spatial queries, analysis, and data manipulation within a relational database environment. While Atlas-DB provides spatial indexing and querying capabilities, it may not offer the same level of geospatial functionality as PostGIS for advanced spatial operations.
Programming Language Support: PostGIS is tightly integrated with PostgreSQL and supports SQL as the primary language for querying and manipulating spatial data. In contrast, Atlas-DB offers SDKs and client libraries for various programming languages such as Java, Python, and Go, enabling developers to interact with the database in their preferred language.
Community and Ecosystem: PostGIS has a large and active community of users and developers, with extensive documentation, tutorials, and third-party tools available for spatial data management. While Atlas-DB has a growing community, it may not have the same level of community support and ecosystem as PostGIS, which could impact the availability of resources and expertise for users.
Use Cases: Atlas-DB is well-suited for real-time, high-throughput applications that require low-latency access to spatial and non-spatial data across distributed systems. In contrast, PostGIS is more commonly used for geographic information systems (GIS), mapping applications, and spatial analysis where relational database functionality is essential for data integrity and consistency.

In Summary, Atlas-DB excels in horizontal scalability and distributed systems, while PostGIS offers robust geospatial functionality within a relational database model, catering to different use cases in spatial data management.

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CLI (Node.js)

Manual

Detailed Comparison

PostGIS	Atlas-DB
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.	Atlas was developed by Netflix to manage dimensional time series data for near real-time operational insight. Atlas features in-memory data storage, allowing it to gather and report very large numbers of metrics, very quickly.
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	Manages dimensional time series data; In-memory data storage; Captures operational intelligence
Statistics
GitHub Stars 2.0K	GitHub Stars 3.5K
GitHub Forks 407	GitHub Forks 324
Stacks 381	Stacks 6
Followers 377	Followers 77
Votes 30	Votes 0
Pros & Cons
Pros 25 De facto GIS in SQL 5 Good Documentation	No community feedback yet
Integrations
PostgreSQL	No integrations available

What are some alternatives to PostGIS, Atlas-DB?

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.

Liquibase

Liquibase is th leading open-source tool for database schema change management. Liquibase helps teams track, version, and deploy database schema and logic changes so they can automate their database code process with their app code process.

Sequel Pro

Sequel Pro is a fast, easy-to-use Mac database management application for working with MySQL databases.

DBeaver

It is a free multi-platform database tool for developers, SQL programmers, database administrators and analysts. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, Teradata, MongoDB, Cassandra, Redis, etc.

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.

Knex.js

Knex.js is a "batteries included" SQL query builder for Postgres, MySQL, MariaDB, SQLite3, and Oracle designed to be flexible, portable, and fun to use. It features both traditional node style callbacks as well as a promise interface for cleaner async flow control, a stream interface, full featured query and schema builders, transaction support (with savepoints), connection pooling and standardized responses between different query clients and dialects.

Flyway

It lets you regain control of your database migrations with pleasure and plain sql. Solves only one problem and solves it well. It migrates your database, so you don't have to worry about it anymore.

Related Comparisons

Atlas-DB vs PostGIS: What are the differences?

Introduction:

Data Model: Atlas-DB is a distributed key-value store with multi-dimensional indexing capabilities, optimized for storing and querying spatial and non-spatial data efficiently. On the other hand, PostGIS is an extension of PostgreSQL, adding support for geographic objects, spatial indexing, and spatial functions within a relational database model.
Scalability: Atlas-DB is designed for horizontal scalability, making it well-suited for large-scale distributed systems where data is spread across multiple nodes for high availability and performance. In contrast, PostGIS is more limited in scalability as it relies on a single relational database instance, which can be a bottleneck for high-traffic applications.
Geospatial Functionality: PostGIS offers a wide range of geospatial functions and capabilities, allowing users to perform complex spatial queries, analysis, and data manipulation within a relational database environment. While Atlas-DB provides spatial indexing and querying capabilities, it may not offer the same level of geospatial functionality as PostGIS for advanced spatial operations.
Programming Language Support: PostGIS is tightly integrated with PostgreSQL and supports SQL as the primary language for querying and manipulating spatial data. In contrast, Atlas-DB offers SDKs and client libraries for various programming languages such as Java, Python, and Go, enabling developers to interact with the database in their preferred language.
Community and Ecosystem: PostGIS has a large and active community of users and developers, with extensive documentation, tutorials, and third-party tools available for spatial data management. While Atlas-DB has a growing community, it may not have the same level of community support and ecosystem as PostGIS, which could impact the availability of resources and expertise for users.
Use Cases: Atlas-DB is well-suited for real-time, high-throughput applications that require low-latency access to spatial and non-spatial data across distributed systems. In contrast, PostGIS is more commonly used for geographic information systems (GIS), mapping applications, and spatial analysis where relational database functionality is essential for data integrity and consistency.

Atlas-DB vs PostGIS

Overview