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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. ArangoDB vs PostgreSQL

ArangoDB vs PostgreSQL

OverviewDecisionsComparisonAlternatives

Overview

PostgreSQL
PostgreSQL
Stacks103.0K
Followers83.9K
Votes3.6K
GitHub Stars19.0K
Forks5.2K
ArangoDB
ArangoDB
Stacks273
Followers442
Votes192

ArangoDB vs PostgreSQL: What are the differences?

Introduction

ArangoDB and PostgreSQL are both popular database management systems (DBMS) used in web development. While they share similarities in being relational databases and offering ACID compliance, there are key differences that set them apart. In this article, we will discuss six of the most significant differences between ArangoDB and PostgreSQL.

  1. Data Model: ArangoDB is a multi-model database that supports document, graph, and key-value models, offering a flexible data model for different use cases. On the other hand, PostgreSQL is a traditional relational database that follows the table-based data model with predefined schemas and strict data types.

  2. Query Language: ArangoDB provides its own query language called AQL (ArangoDB Query Language), which is SQL-like and allows for flexible querying across different data models. In contrast, PostgreSQL uses SQL (Structured Query Language), the standard language for querying and managing relational databases.

  3. Scalability: ArangoDB provides both horizontal and vertical scalability, allowing for efficient scaling as the data and workload expand. It achieves this through sharding and replication. On the other hand, PostgreSQL has limited built-in scalability features and typically relies on vertical scaling with hardware upgrades.

  4. Concurrency Control: ArangoDB utilizes a multi-version concurrency control (MVCC) system, allowing concurrent read and write operations without locking the entire database. This improves concurrency and performance. PostgreSQL also supports MVCC but implements it differently, with a focus on protecting data consistency over performance.

  5. Joins: PostgreSQL is widely known for its advanced support of complex SQL queries and joins, making it a preferable choice for applications with complex relationships and data hierarchies. While ArangoDB can handle simpler joins, it may not be as powerful or efficient in handling complex join operations.

  6. Community and Ecosystem: PostgreSQL has been around for a long time and has a large and active community. It has a mature ecosystem with numerous extensions, tools, and frameworks built around it. ArangoDB, although gaining popularity, has a smaller community and ecosystem in comparison.

In summary, ArangoDB stands out with its multi-model capabilities, AQL query language, and scalable architecture, while PostgreSQL excels in its advanced SQL support, data consistency focus, and mature ecosystem. The choice between the two would depend on specific use cases and priorities.

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Advice on PostgreSQL, ArangoDB

Kyle
Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

DecidedonPostGISPostGIS

While there's been some very clever techniques that has allowed non-natively supported geo querying to be performed, it is incredibly slow in the long game and error prone at best.

MySQL finally introduced it's own GEO functions and special indexing operations for GIS type data. I prototyped with this, as MySQL is the most familiar database to me. But no matter what I did with it, how much tuning i'd give it, how much I played with it, the results would come back inconsistent.

It was very disappointing.

I figured, at this point, that SQL Server, being an enterprise solution authored by one of the biggest worldwide software developers in the world, Microsoft, might contain some decent GIS in it.

I was very disappointed.

Postgres is a Database solution i'm still getting familiar with, but I noticed it had no built in support for GIS. So I hilariously didn't pay it too much attention. That was until I stumbled upon PostGIS and my world changed forever.

449k views449k
Comments
George
George

Student

Mar 18, 2020

Needs adviceonPostgreSQLPostgreSQLPythonPythonDjangoDjango

Hello everyone,

Well, I want to build a large-scale project, but I do not know which ORDBMS to choose. The app should handle real-time operations, not chatting, but things like future scheduling or reminders. It should be also really secure, fast and easy to use. And last but not least, should I use them both. I mean PostgreSQL with Python / Django and MongoDB with Node.js? Or would it be better to use PostgreSQL with Node.js?

*The project is going to use React for the front-end and GraphQL is going to be used for the API.

Thank you all. Any answer or advice would be really helpful!

620k views620k
Comments
Navraj
Navraj

CEO at SuPragma

Apr 16, 2020

Needs adviceonMySQLMySQLPostgreSQLPostgreSQL

I asked my last question incorrectly. Rephrasing it here.

I am looking for the most secure open source database for my project I'm starting: https://github.com/SuPragma/SuPragma/wiki

Which database is more secure? MySQL or PostgreSQL? Are there others I should be considering? Is it possible to change the encryption keys dynamically?

Thanks,

Raj

401k views401k
Comments

Detailed Comparison

PostgreSQL
PostgreSQL
ArangoDB
ArangoDB

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.

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

-
multi-model nosql db; acid; transactions; javascript; database; nosql; sharding; replication; query language; joins; aql; documents; graphs; key-values; graphdb
Statistics
GitHub Stars
19.0K
GitHub Stars
-
GitHub Forks
5.2K
GitHub Forks
-
Stacks
103.0K
Stacks
273
Followers
83.9K
Followers
442
Votes
3.6K
Votes
192
Pros & Cons
Pros
  • 765
    Relational database
  • 511
    High availability
  • 439
    Enterprise class database
  • 383
    Sql
  • 304
    Sql + nosql
Cons
  • 10
    Table/index bloatings
Pros
  • 37
    Grahps and documents in one DB
  • 26
    Intuitive and rich query language
  • 25
    Open source
  • 25
    Good documentation
  • 21
    Joins for collections
Cons
  • 3
    Web ui has still room for improvement
  • 2
    No support for blueprints standard, using custom AQL

What are some alternatives to PostgreSQL, ArangoDB?

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.

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.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

CouchDB

CouchDB

Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.

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