DBMS > GBase vs. Hive vs. Microsoft Azure SQL Database vs. XTDB

System Properties Comparison GBase vs. Hive vs. Microsoft Azure SQL Database vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Database as a Service offering with high compatibility to Microsoft SQL Server

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.gbase.cn

hive.apache.org

azure.microsoft.com/en-us/products/azure-sql/database

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

docs.microsoft.com/en-us/azure/azure-sql

www.xtdb.com/docs

Developer

General Data Technology Co., Ltd.

Apache Software Foundation

initially developed by Facebook

Microsoft

Juxt Ltd.

Initial release

2004

2012

2010

2019

Current release

GBase 8a, GBase 8s, GBase 8c

3.1.3, April 2022

V12

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

MIT License

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++

Clojure

Server operating systems

Linux

All OS with a Java VM

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL-like DML and DDL statements

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

C++
Java
PHP
Python

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

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes, with always 3 replicas available

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

User concepts

Access control

yes

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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More resources

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