DBMS > Amazon DynamoDB vs. EsgynDB vs. Kyligence Enterprise vs. OrigoDB vs. Titan

System Properties Comparison Amazon DynamoDB vs. EsgynDB vs. Kyligence Enterprise vs. OrigoDB 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

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

A distributed analytics engine for big data, built on top of Apache Kylin

A fully ACID in-memory object graph database

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Object oriented DBMS

Graph DBMS

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

Score	72.39
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.15
Rank	#325	Overall
	#145	Relational DBMS

Score	0.46
Rank	#253	Overall
	#117	Relational DBMS

Score	0.00
Rank	#386	Overall
	#54	Document stores
	#20	Object oriented DBMS

Website

aws.amazon.com/dynamodb

www.esgyn.cn

kyligence.io/kyligence-enterprise

origodb.com

github.com/thinkaurelius/titan

Technical documentation

docs.aws.amazon.com/dynamodb

origodb.com/docs

github.com/thinkaurelius/titan/wiki

Developer

Amazon

Esgyn

Kyligence, Inc.

Robert Friberg et al

Aurelius, owned by DataStax

Initial release

2012

2015

2016

2009

under the name LiveDB

2012

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

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++, Java

Java

Server operating systems

hosted

Linux

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

.NET Client API
HTTP API
LINQ

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

.Net

Clojure
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

Source-replica replication

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Write ahead log

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.

yes

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

Role based authorization

User authentification and security via Rexster Graph Server

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