DBMS > Badger vs. Citus vs. SpaceTime vs. VoltDB

System Properties Comparison Badger vs. Citus vs. SpaceTime vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

SpaceTime is a spatio-temporal DBMS with a focus on performance.

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

Secondary database models

Document store

Relational DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

github.com/dgraph-io/badger

www.citusdata.com

www.mireo.com/spacetime

www.voltdb.com

Technical documentation

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

docs.citusdata.com

docs.voltdb.com

Developer

DGraph Labs

Mireo

VoltDB Inc.

Initial release

2017

2010

2020

2010

Current release

8.1, December 2018

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL, commercial license also available

commercial

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++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X

for development

Data scheme

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

A subset of ANSI SQL is implemented

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
C++
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Fixed-grid hypercubes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

other methods possible by using 3rd party extensions

Real-time block device replication (DRBD)

Multi-source replication
Source-replica replication

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

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

yes

Users and roles with access to stored procedures

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