DBMS > Altibase vs. Google BigQuery vs. NuoDB vs. RavenDB vs. Transbase

System Properties Comparison Altibase vs. Google BigQuery vs. NuoDB vs. RavenDB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Large scale data warehouse service with append-only tables

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

altibase.com

cloud.google.com/bigquery

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

ravendb.net

www.transaction.de/en/products/transbase.html

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

cloud.google.com/bigquery/docs

doc.nuodb.com

ravendb.net/docs

www.transaction.de/en/products/transbase/features.html

Developer

Altibase

Google

Dassault Systèmes

originally NuoDB, Inc.

Hibernating Rhinos

Transaction Software GmbH

Initial release

1999

2010

2013

2010

1987

Current release

v7.3, 2023, August 2023

5.4, July 2022

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

limited edition free

Open Source

AGPL version 3, commercial license available

commercial

free development license

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++

C and C++

Server operating systems

AIX
HP-UX
Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

yes

SQL-like query language (RQL)

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C++
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

in JavaScript

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Managed transparently by NuoDB

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

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, Cluster-wide transaction available

yes

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

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

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

Standard SQL roles/ privileges, Administrative Users

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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