DBMS > Amazon DocumentDB vs. BigObject vs. HEAVY.AI vs. MySQL vs. NuoDB

System Properties Comparison Amazon DocumentDB vs. BigObject vs. HEAVY.AI vs. MySQL vs. NuoDB

Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for real-time computations and queries

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Widely used open source RDBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Document store

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

aws.amazon.com/documentdb

bigobject.io

github.com/heavyai/heavydb
www.heavy.ai

www.mysql.com

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

aws.amazon.com/documentdb/resources

Developer

BigObject, Inc.

HEAVY.AI, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2019

2015

2016

1995

2013

Current release

5.10, January 2022

8.4.0, April 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

limited edition free

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C++ and CUDA

C and C++

C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

yes

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC/Thrift
Python

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

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-source replication

Multi-source replication
Source-replica replication

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

automatically between fact table and dimension tables

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Atomic single-document operations

ACID

not for MyISAM storage engine

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

table locks or row locks depending on storage engine

yes

MVCC

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

Temporary table

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Standard SQL roles/ privileges, Administrative Users

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.