DBMS > Amazon Aurora vs. Amazon DocumentDB vs. Vertica

System Properties Comparison Amazon Aurora vs. Amazon DocumentDB vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Document store

Relational DBMS

Column oriented

Secondary database models

Document store

Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	8.11
Rank	#44	Overall
	#28	Relational DBMS

Score	1.85
Rank	#125	Overall
	#22	Document stores

Score	9.63
Rank	#42	Overall
	#26	Relational DBMS

Website

aws.amazon.com/rds/aurora

aws.amazon.com/documentdb

www.vertica.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

aws.amazon.com/documentdb/resources

vertica.com/documentation

Developer

Amazon

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2015

2019

2005

Current release

12.0.3, January 2023

License

Commercial or Open Source

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

Linux

Data scheme

yes

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

ADO.NET
JDBC
ODBC

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
Java
JavaScript (Node.js)
PHP
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

Recent citations in the news

Vacasa’s migration to Amazon Aurora for a more efficient Property Management System
9 January 2025, AWS Blog

Introducing Amazon Aurora DSQL | Amazon Web Services
3 December 2024, AWS Blog

Amazon Aurora PostgreSQL Limitless Database is now generally available
31 October 2024, AWS Blog

Introducing scaling to 0 capacity with Amazon Aurora Serverless v2
20 November 2024, AWS Blog

Introducing scaling up to 256 ACUs with Amazon Aurora Serverless v2
8 October 2024, AWS Blog

provided by Google News

Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service is now available
16 May 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0
15 April 2024, AWS Blog

Unlock the power of parallel indexing in Amazon DocumentDB
19 June 2024, AWS Blog

Optimizing costs on Amazon DocumentDB using event-driven architecture and the AWS EventBridge Terraform module
23 August 2024, AWS Blog

Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot
20 May 2024, AWS Blog

provided by Google News

Introducing the Future of Data Analysis: A Revolutionary Tool for Vertica Users
25 October 2024, blogs.opentext.com

Vertica on Kubernetes
20 June 2024, blogs.opentext.com

Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK
11 February 2021, AWS Blog

Solving Big Data Challenges with Data Science at Uber
20 March 2019, Uber

New browser-based query editor for OpenText Core Analytics Database accelerates and simplifies querying your data
25 November 2024, blogs.opentext.com

provided by Google News

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