DBMS > ArcadeDB vs. GBase vs. Graphite vs. HBase

System Properties Comparison ArcadeDB vs. GBase vs. Graphite vs. HBase

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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

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Time Series DBMS

Wide column store

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	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Website

arcadedb.com

www.gbase.cn

github.com/graphite-project/graphite-web

hbase.apache.org

Technical documentation

docs.arcadedb.com

graphite.readthedocs.io

hbase.apache.org/book.html

Developer

Arcade Data

General Data Technology Co., Ltd.

Chris Davis

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

2021

2004

2006

2008

Current release

September 2021

GBase 8a, GBase 8s, GBase 8c

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

Apache version 2

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, Java, Python

Python

Java

Server operating systems

All OS with a Java VM

Linux

Linux
Unix

Linux
Unix
Windows

using Cygwin

Data scheme

schema-free

yes

schema-free, schema definition possible

Typing

predefined data types such as float or date

yes

Numeric data only

options to bring your own types, AVRO

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

SQL-like query language, no joins

Standard with numerous extensions

APIs and other access methods

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

ADO.NET
C API
JDBC
ODBC

HTTP API
Sockets

Java API
RESTful HTTP API
Thrift

Supported programming languages

Java

JavaScript (Node.js)
Python

C
C#
C++
Groovy
Java
PHP
Python
Scala

Server-side scripts

Stored procedures

user defined functions

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

Multi-source 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

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)

Concurrency

Support for concurrent manipulation of data

yes

locking

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

yes

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

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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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

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