DBMS > ArcadeDB vs. Badger vs. HBase vs. openGauss

System Properties Comparison ArcadeDB vs. Badger vs. HBase vs. openGauss

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Key-value store

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	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Website

arcadedb.com

github.com/dgraph-io/badger

hbase.apache.org

gitee.com/opengauss
opengauss.org

Technical documentation

docs.arcadedb.com

godoc.org/github.com/dgraph-io/badger

hbase.apache.org/book.html

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

Developer

Arcade Data

DGraph Labs

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Huawei and openGauss community

Initial release

2021

2017

2008

2019

Current release

September 2021

2.3.4, January 2021

3.0, March 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

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

Java

C, C++, Java

Server operating systems

All OS with a Java VM

BSD
Linux
OS X
Solaris
Windows

Linux
Unix
Windows

using Cygwin

Linux

Data scheme

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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 query language, no joins

ANSI SQL 2011

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

Java API
RESTful HTTP API
Thrift

JDBC
ODBC

Supported programming languages

Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Java

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning (by range, list and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

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

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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

show all

Recent citations in the news

MapR Technologies' Executives to Speak About Big Data, HBase and Hadoop at Upcoming April Conferences
10 May 2024, Yahoo Movies UK

Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ...
9 October 2023, AWS Blog

Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase
20 October 2023, hackernoon.com

HBase: The database big data left behind
6 May 2016, InfoWorld

HBase Tutorial
24 February 2023, Simplilearn

provided by Google News

openGauss Open Source Community Officially Launch
1 July 2020, Huawei

The openGauss powers database industry forward through innovation
6 January 2022, Global Times

About HUAWEI Open Source
9 February 2022, Huawei

provided by Google News

Share this page