DBMS > gStore vs. HBase vs. RocksDB vs. VoltDB

System Properties Comparison gStore vs. HBase vs. RocksDB vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

A native Graph DBMS to store and maintain very large RDF datasets.

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

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

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

Score	0.14
Rank	#342	Overall
	#34	Graph DBMS
	#16	RDF stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

Technical documentation

en.gstore.cn/#/enDocs

hbase.apache.org/book.html

github.com/facebook/rocksdb/wiki

docs.voltdb.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Facebook, Inc.

VoltDB Inc.

Initial release

2016

2008

2013

2010

Current release

1.2, November 2023

2.3.4, January 2021

9.2.1, May 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache version 2

Open Source

BSD

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

Java

C++

Java, C++

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

Linux

Linux
OS X

for development

Data scheme

schema-free and OWL/RDFS-schema support

schema-free, schema definition possible

schema-free

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

yes

only a subset of SQL 99

APIs and other access methods

HTTP API
SPARQL 1.1

Java API
RESTful HTTP API
Thrift

C++ API
Java API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
Java
JavaScript (Node.js)
PHP
Python

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

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 or Eventual Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

Single row ACID (across millions of columns)

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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

Users and roles with access to stored procedures

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