DBMS > GBase vs. Hive vs. Sequoiadb vs. StarRocks

System Properties Comparison GBase vs. Hive vs. Sequoiadb vs. StarRocks

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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

NewSQL database with distributed OLTP and SQL

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Relational DBMS

Document store
Relational DBMS

Relational DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

Technical documentation

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

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

General Data Technology Co., Ltd.

Apache Software Foundation

initially developed by Facebook

Sequoiadb Ltd.

The Linux Foundation

since Feb 2023

Initial release

2004

2012

2013

2020

Current release

GBase 8a, GBase 8s, GBase 8c

3.1.3, April 2022

2.5.3, March 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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++

C++, Java

Server operating systems

Linux

All OS with a Java VM

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
Thrift

proprietary protocol using JSON

JDBC
MySQL protocol

Supported programming languages

C++
Java
PHP
Python

.Net
C++
Java
PHP
Python

Java

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

JavaScript

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

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

Document is locked during a transaction

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 rights for users, groups and roles

simple password-based access control

Role based access control and fine grained access rights

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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