DBMS > BigObject vs. Hypertable vs. openGauss vs. StarRocks

System Properties Comparison BigObject vs. Hypertable vs. openGauss vs. StarRocks

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Analytic DBMS for real-time computations and queries

An open source BigTable implementation based on distributed file systems such as Hadoop

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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

a hierachical model (tree) can be imposed

Wide column store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

bigobject.io

gitee.com/opengauss
opengauss.org

www.starrocks.io

Technical documentation

docs.bigobject.io

docs.opengauss.org/en
gitee.com/opengauss/docs

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

Developer

BigObject, Inc.

Hypertable Inc.

Huawei and openGauss community

The Linux Foundation

since Feb 2023

Initial release

2015

2009

2019

2020

Current release

0.9.8.11, March 2016

3.0, March 2022

2.5.3, March 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C, C++, Java

C++, Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL 2011

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

C++ API
Thrift

JDBC
ODBC

JDBC
MySQL protocol

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C
C++
Java

Java

Server-side scripts

Stored procedures

Lua

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning (by range, list and hash)

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor on file system level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Role based access control and fine grained access rights

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