DBMS > Amazon DynamoDB vs. AnzoGraph DB vs. Datomic vs. MonetDB vs. RocksDB

System Properties Comparison Amazon DynamoDB vs. AnzoGraph DB vs. Datomic vs. MonetDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A relational database management system that stores data in columns

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store
Key-value store

Graph DBMS
RDF store

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

aws.amazon.com/dynamodb

cambridgesemantics.com/anzograph

www.datomic.com

www.monetdb.org

rocksdb.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.datomic.com

www.monetdb.org/Documentation

github.com/facebook/rocksdb/wiki

Developer

Amazon

Cambridge Semantics

Cognitect

MonetDB BV

Facebook, Inc.

Initial release

2012

2018

2012

2004

2013

Current release

2.3, January 2021

1.0.7075, December 2023

Dec2023 (11.49), December 2023

9.2.1, May 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free trial version available

commercial

limited edition free

Open Source

Mozilla Public License 2.0

Open Source

BSD

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

Java, Clojure

C++

Server operating systems

hosted

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

yes

schema-free

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

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

SQL 2003 with some extensions

APIs and other access methods

RESTful HTTP API

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

C++ API
Java API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
Python

Clojure
Java

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Transaction Functions

yes, in SQL, C, R

Triggers

yes

by integration with AWS Lambda

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

none

But extensive use of caching in the application peers

Sharding via remote tables

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

none

But extensive use of caching in the application peers

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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.