DBMS > BigObject vs. openGauss vs. RocksDB

System Properties Comparison BigObject vs. openGauss vs. RocksDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	0.23
Rank	#345	Overall
	#153	Relational DBMS

Score	1.35
Rank	#194	Overall
	#93	Relational DBMS

Score	3.92
Rank	#94	Overall
	#15	Key-value stores

Website

bigobject.io

gitee.com/opengauss
opengauss.org

rocksdb.org

Technical documentation

docs.bigobject.io

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

github.com/facebook/rocksdb/wiki

Developer

BigObject, Inc.

Huawei and openGauss community

Facebook, Inc.

Initial release

2015

2019

2013

Current release

3.0, March 2022

7.10.2, March 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

BSD

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, C++, Java

C++

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

Data scheme

yes

schema-free

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

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL 2011

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

C++ API
Java API

Supported programming languages

C
C++
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash)

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.