DBMS > Amazon DynamoDB vs. Apache Jena - TDB vs. EsgynDB vs. GeoMesa vs. Titan

System Properties Comparison Amazon DynamoDB vs. Apache Jena - TDB vs. EsgynDB vs. GeoMesa 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

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Document store
Key-value store

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	3.75
Rank	#84	Overall
	#3	RDF stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Website

aws.amazon.com/dynamodb

jena.apache.org/documentation/tdb/index.html

www.esgyn.cn

www.geomesa.org

github.com/thinkaurelius/titan

Technical documentation

docs.aws.amazon.com/dynamodb

jena.apache.org/documentation/tdb/index.html

www.geomesa.org/documentation/stable/user/index.html

github.com/thinkaurelius/titan/wiki

Developer

Amazon

Apache Software Foundation

originally developed by HP Labs

Esgyn

CCRi and others

Aurelius, owned by DataStax

Initial release

2012

2000

2015

2014

2012

Current release

4.9.0, July 2023

4.0.5, February 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache License, Version 2.0

commercial

Open Source

Apache 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

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Implementation language

Java

C++, Java

Scala

Java

Server operating systems

hosted

All OS with a Java VM

Linux

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

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

APIs and other access methods

RESTful HTTP API

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java

All languages supporting JDBC/ODBC/ADO.Net

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

depending on storage layer

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication between multi datacenters

depending on storage layer

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

Immediate Consistency

depending on storage layer

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

TDB Transactions

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.

depending on storage layer

User concepts

Access control

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

Access control via Jena Security

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

User authentification and security via Rexster Graph Server

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