DBMS > Amazon DynamoDB vs. Cachelot.io vs. EsgynDB vs. MonetDB vs. Titan

System Properties Comparison Amazon DynamoDB vs. Cachelot.io vs. EsgynDB vs. MonetDB vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

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

In-memory caching system

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A relational database management system that stores data in columns

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Document store
Key-value store

Key-value store

Relational DBMS

Graph DBMS

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	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Website

aws.amazon.com/dynamodb

cachelot.io

www.esgyn.cn

www.monetdb.org

github.com/thinkaurelius/titan

Technical documentation

docs.aws.amazon.com/dynamodb

www.monetdb.org/Documentation

github.com/thinkaurelius/titan/wiki

Developer

Amazon

Esgyn

MonetDB BV

Aurelius, owned by DataStax

Initial release

2012

2015

2004

2012

Current release

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Simplified BSD License

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache license, version 2.0

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

C++

C++, Java

Java

Server operating systems

hosted

FreeBSD
Linux
OS X

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

RESTful HTTP API

Memcached protocol

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

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

Clojure
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes, in SQL, C, R

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Sharding via remote tables

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication between multi datacenters

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)

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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