DBMS > Badger vs. EsgynDB vs. gStore vs. Riak KV vs. VoltDB

System Properties Comparison Badger vs. EsgynDB vs. gStore vs. Riak KV vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Distributed, fault tolerant key-value store

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

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

github.com/dgraph-io/badger

www.esgyn.cn

en.gstore.cn

www.voltdb.com

Technical documentation

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

en.gstore.cn/#/enDocs

www.tiot.jp/riak-docs/riak/kv/latest

docs.voltdb.com

Developer

DGraph Labs

Esgyn

OpenSource, formerly Basho Technologies

VoltDB Inc.

Initial release

2017

2015

2016

2009

2010

Current release

1.2, November 2023

3.2.0, December 2022

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD

Open Source

Apache version 2, commercial enterprise edition

Open Source

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

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++, Java

C++

Erlang

Java, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X

for development

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

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

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API
SPARQL 1.1

HTTP API
Native Erlang Interface

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Erlang

Java

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

selectable replication factor

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

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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

yes, using Riak Security

Users and roles with access to stored procedures

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More resources

Recent citations in the news

Basho Revamps Riak Open-Source Database
22 September 2023, InformationWeek

Riak NoSQL Database: Use Cases and Best Practices
23 December 2011, InfoQ.com

Basho, Maker of Riak NoSQL Database, Raises $25M
13 January 2015, Data Center Knowledge

Riak NoSQL snapped up by Bet365
12 September 2017, ComputerWeekly.com

Riak Taps Mesos for 'Push Button' NoSQL Scalability
20 August 2015, Datanami

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31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

provided by Google News

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