DBMS > Alibaba Cloud Table Store vs. Google BigQuery vs. Kingbase vs. Oracle NoSQL

System Properties Comparison Alibaba Cloud Table Store vs. Google BigQuery vs. Kingbase vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Large scale data warehouse service with append-only tables

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

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

Primary database model

Wide column store

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.24
Rank	#310	Overall
	#12	Wide column stores

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.45
Rank	#265	Overall
	#124	Relational DBMS

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Website

www.alibabacloud.com/product/table-store

cloud.google.com/bigquery

www.kingbase.com.cn

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

Technical documentation

www.alibabacloud.com/help/en/tablestore

cloud.google.com/bigquery/docs

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

Developer

Alibaba

Google

BeiJing KINGBASE Information technologies inc.

Oracle

Initial release

2016

2010

1999

2011

Current release

V8.0, August 2021

23.3, December 2023

License

Commercial or Open Source

commercial

Open Source

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

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 and Java

Java

Server operating systems

hosted

Linux
Windows

Linux
Solaris SPARC/x86

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

optional

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

yes

Standard with numerous extensions

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

RESTful HTTP/JSON API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

RESTful HTTP API

Supported programming languages

Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

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

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

Since BigQuery is designed for querying data

ACID

configurable

ACID within a storage node (=shard)

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

User concepts

Access control

Access rights based on subaccounts and tokens

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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