DBMS > Amazon Neptune vs. Hypertable vs. Microsoft Azure Cosmos DB vs. OrigoDB

System Properties Comparison Amazon Neptune vs. Hypertable vs. Microsoft Azure Cosmos DB vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Fast, reliable graph database built for the cloud

An open source BigTable implementation based on distributed file systems such as Hadoop

Globally distributed, horizontally scalable, multi-model database service

A fully ACID in-memory object graph database

Primary database model

Graph DBMS
RDF store

Wide column store

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#19	Object oriented DBMS

Website

aws.amazon.com/neptune

azure.microsoft.com/services/cosmos-db

origodb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

learn.microsoft.com/azure/cosmos-db

origodb.com/docs

Developer

Amazon

Hypertable Inc.

Microsoft

Robert Friberg et al

Initial release

2017

2009

2014

2009

under the name LiveDB

Current release

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

Open Source

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++

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

User defined using .NET types and collections

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

restricted

only exact value or prefix value scans

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

C++ API
Thrift

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

.NET Client API
HTTP API
LINQ

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C++
Java
Perl
PHP
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

JavaScript

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

selectable replication factor on file system level

yes

Implicit feature of the cloud service

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

depending on model

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

Write ahead log

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)

Access rights can be defined down to the item level

Role based authorization

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