DBMS > Amazon DynamoDB vs. BigchainDB vs. Microsoft Access vs. RavenDB vs. RDF4J

System Properties Comparison Amazon DynamoDB vs. BigchainDB vs. Microsoft Access vs. RavenDB vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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.)

Open Source Operational and Transactional Enterprise NoSQL Document Database

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store
Key-value store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

aws.amazon.com/dynamodb

www.bigchaindb.com

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

ravendb.net

rdf4j.org

Technical documentation

docs.aws.amazon.com/dynamodb

bigchaindb.readthedocs.io/en/latest

developer.microsoft.com/en-us/access

ravendb.net/docs

rdf4j.org/documentation

Developer

Amazon

Microsoft

Hibernating Rhinos

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2012

2016

1992

2010

2004

Current release

1902 (16.0.11328.20222), March 2019

5.4, July 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL v3

commercial

Bundled with Microsoft Office

Open Source

AGPL version 3, commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

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.

Implementation language

Python

C++

Java

Server operating systems

hosted

Linux

Windows

Not a real database server, but making use of DLLs

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

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.

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language (RQL)

APIs and other access methods

RESTful HTTP API

CLI Client
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Haskell
Java
JavaScript
Python
Ruby

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

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

Java
PHP
Python

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

yes

Triggers

yes

by integration with AWS Lambda

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

but no files for transaction logging

ACID, Cluster-wide transaction available

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

but no files for transaction logging

yes

in-memory storage is supported as well

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes

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

Authorization levels configured per client per database

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.