DBMS > Badger vs. BigchainDB vs. Ingres vs. VoltDB

System Properties Comparison Badger vs. BigchainDB vs. Ingres 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.

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Well established RDBMS

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

Key-value store

Document store

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	0.79
Rank	#212	Overall
	#36	Document stores

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

github.com/dgraph-io/badger

www.bigchaindb.com

www.actian.com/databases/ingres

www.voltdb.com

Technical documentation

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

bigchaindb.readthedocs.io/en/latest

docs.actian.com/ingres

docs.voltdb.com

Developer

DGraph Labs

Actian Corporation

VoltDB Inc.

Initial release

2017

2016

1974

originally developed at University Berkely in early 1970s

2010

Current release

11.2, May 2022

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL v3

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

Python

Java, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

CLI Client
RESTful HTTP API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Ingres Replicator

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

MVCC

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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