DBMS > Amazon DocumentDB vs. Graph Engine vs. HEAVY.AI vs. Microsoft Access vs. MySQL

System Properties Comparison Amazon DocumentDB vs. Graph Engine vs. HEAVY.AI vs. Microsoft Access vs. MySQL

Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used open source RDBMS

Primary database model

Document store

Graph DBMS
Key-value store

Relational DBMS

Key/Value like access via memcached API

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	#131	Overall
	#24	Document stores

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

aws.amazon.com/documentdb

www.graphengine.io

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

www.microsoft.com/en-us/microsoft-365/access

www.mysql.com

Technical documentation

aws.amazon.com/documentdb/resources

www.graphengine.io/docs/manual

docs.heavy.ai

developer.microsoft.com/en-us/access

dev.mysql.com/doc

Developer

Microsoft

HEAVY.AI, Inc.

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2019

2010

2016

1992

1995

Current release

5.10, January 2022

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache Version 2; enterprise edition available

commercial

Bundled with Microsoft Office

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

.NET and C

C++ and CUDA

C++

C and C++

Server operating systems

hosted

.NET

Linux

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
OS X
Solaris
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

yes

but not compliant to any SQL standard

yes

with proprietary extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Round robin

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

none

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-document operations

ACID

but no files for transaction logging

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

but no files for transaction logging

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

Access rights for users and roles

fine grained access rights according to SQL-standard

a simple user-level security was built in till version Access 2003

Users with fine-grained authorization concept

no user groups or roles

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