DBMS > Hyprcubd vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. NuoDB vs. Yaacomo

System Properties Comparison Hyprcubd vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. NuoDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Serverless Time Series DBMS

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Globally distributed, horizontally scalable, multi-model database service

NuoDB is a webscale distributed database that supports SQL and ACID transactions

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

hyprcubd.com (offline)

janusgraph.org

azure.microsoft.com/services/cosmos-db

www.3ds.com/nuodb-distributed-sql-database

yaacomo.com

Technical documentation

docs.janusgraph.org

learn.microsoft.com/azure/cosmos-db

doc.nuodb.com

Developer

Hyprcubd, Inc.

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Q2WEB GmbH

Initial release

2017

2014

2013

2009

Current release

0.6.3, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

limited edition free

commercial

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

C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC (https)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Clojure
Java
Python

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

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript

Java, SQL

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

data is dynamically stored/cached on the nodes where it is read/written

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Managed transparently by NuoDB

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

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

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

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

yes

Temporary table

yes

User concepts

Access control

token access

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

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