DBMS > GBase vs. Google BigQuery vs. STSdb vs. Teradata Aster vs. ToroDB

System Properties Comparison GBase vs. Google BigQuery vs. STSdb vs. Teradata Aster vs. ToroDB

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

ToroDB 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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Platform for big data analytics on multistructured data sources and types

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

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	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

www.gbase.cn

cloud.google.com/bigquery

github.com/STSSoft/STSdb4

github.com/torodb/server

Technical documentation

cloud.google.com/bigquery/docs

Developer

General Data Technology Co., Ltd.

Google

STS Soft SC

Teradata

8Kdata

Initial release

2004

2010

2011

2005

2016

Current release

GBase 8a, GBase 8s, GBase 8c

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

GPLv2, commercial license available

commercial

Open Source

AGPL-V3

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

Windows

Linux

All OS with a Java 7 VM

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

yes

string, integer, double, boolean, date, object_id

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

RESTful HTTP/JSON API

.NET Client API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

in JavaScript

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
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

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.

User concepts

Access control

yes

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users and roles

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