DBMS > GBase vs. Google BigQuery vs. Oracle NoSQL vs. SAP Advantage Database Server

System Properties Comparison GBase vs. Google BigQuery vs. Oracle NoSQL vs. SAP Advantage Database Server

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Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. 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.

Large scale data warehouse service with append-only tables

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Website

www.gbase.cn

cloud.google.com/bigquery

www.oracle.com/database/nosql/technologies/nosql

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

Technical documentation

cloud.google.com/bigquery/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

General Data Technology Co., Ltd.

Google

Oracle

Sybase, SAP

Initial release

2004

2010

2011

1993

Current release

GBase 8a, GBase 8s, GBase 8c

24.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

C, Java, Python

Java

Server operating systems

Linux

hosted

Linux
Solaris SPARC/x86

Linux
Windows

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

RESTful HTTP/JSON API

RESTful HTTP API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
Go
Java
JavaScript (Node.js)
Python

Delphi
Perl
PHP

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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

configurable

ACID within a storage node (=shard)

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.

yes

off heap cache

caching of (temporary) tables can be configured

User concepts

Access control

yes

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

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles

fine grained access rights according to SQL-standard

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