DBMS > AnzoGraph DB vs. GBase vs. Google BigQuery vs. NuoDB vs. TimesTen

System Properties Comparison AnzoGraph DB vs. GBase vs. Google BigQuery vs. NuoDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

Large scale data warehouse service with append-only tables

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

In-Memory RDBMS compatible to Oracle

Primary database model

Graph DBMS
RDF store

Relational DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.gbase.cn

cloud.google.com/bigquery

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

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

cloud.google.com/bigquery/docs

doc.nuodb.com

docs.oracle.com/database/timesten-18.1

Developer

Cambridge Semantics

General Data Technology Co., Ltd.

Google

Dassault Systèmes

originally NuoDB, Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2018

2004

2010

2013

1998

Current release

2.3, January 2021

GBase 8a, GBase 8s, GBase 8c

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free trial version available

commercial

limited edition free

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, Java, Python

C++

Server operating systems

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

Standard with numerous extensions

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

ADO.NET
C API
JDBC
ODBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C++
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

in JavaScript

Java, SQL

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

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

none

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Managed transparently by NuoDB

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

Access rights for users and roles

yes

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

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