DBMS > GBase vs. Google Cloud Spanner vs. Newts vs. SAP Advantage Database Server vs. Trafodion

System Properties Comparison GBase vs. Google Cloud Spanner vs. Newts vs. SAP Advantage Database Server vs. Trafodion

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Time Series DBMS based on Cassandra

Low-cost RDBMS with access to ISAM and FoxPro data structures

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

www.gbase.cn

cloud.google.com/spanner

opennms.github.io/newts

www.sap.com/products/advantage-database-server.html

trafodion.apache.org

Technical documentation

cloud.google.com/spanner/docs

github.com/OpenNMS/newts/wiki

trafodion.apache.org/documentation.html

Developer

General Data Technology Co., Ltd.

Google

OpenNMS Group

Sybase, SAP

Apache Software Foundation, originally developed by HP

Initial release

2004

2017

2014

1993

2014

Current release

GBase 8a, GBase 8s, GBase 8c

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

Java

C++, Java

Server operating systems

Linux

hosted

Linux
OS X
Windows

Linux
Windows

Linux

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP REST
Java API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

Java

Delphi
Perl
PHP

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

selectable replication factor

based on Cassandra

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

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.

caching of (temporary) tables can be configured

User concepts

Access control

yes

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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