DBMS > BigObject vs. GBase vs. Hyprcubd vs. Microsoft Azure Cosmos DB vs. NuoDB

System Properties Comparison BigObject vs. GBase vs. Hyprcubd vs. Microsoft Azure Cosmos DB vs. NuoDB

Editorial information provided by DB-Engines

Name

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

Description

Analytic DBMS for real-time computations and queries

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Serverless Time Series DBMS

Globally distributed, horizontally scalable, multi-model database service

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series 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	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational 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

bigobject.io

www.gbase.cn

hyprcubd.com (offline)

azure.microsoft.com/services/cosmos-db

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

Technical documentation

docs.bigobject.io

learn.microsoft.com/azure/cosmos-db

doc.nuodb.com

Developer

BigObject, Inc.

General Data Technology Co., Ltd.

Hyprcubd, Inc.

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2015

2004

2014

2013

Current release

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

commercial

free community edition available

commercial

limited edition free

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, Python

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Standard with numerous extensions

SQL-like query language

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

gRPC (https)

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

ADO.NET
JDBC
ODBC

Supported programming languages

.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

Lua

user defined functions

JavaScript

Java, SQL

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Implicit feature of the cloud service

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

MVCC

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Temporary table

User concepts

Access control

yes

token access

Access rights can be defined down to the item level

Standard SQL roles/ privileges, Administrative Users

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.