DBMS > Badger vs. BigchainDB vs. CouchDB vs. HEAVY.AI vs. Oracle

System Properties Comparison Badger vs. BigchainDB vs. CouchDB vs. HEAVY.AI vs. Oracle

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

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Widely used RDBMS

Primary database model

Key-value store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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	9.30
Rank	#45	Overall
	#7	Document stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

github.com/dgraph-io/badger

www.bigchaindb.com

couchdb.apache.org

github.com/heavyai/heavydb
www.heavy.ai

www.oracle.com/database

Technical documentation

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

bigchaindb.readthedocs.io/en/latest

docs.couchdb.org/en/stable

docs.heavy.ai

docs.oracle.com/en/database

Developer

DGraph Labs

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

HEAVY.AI, Inc.

Oracle

Initial release

2017

2016

2005

2016

1980

Current release

3.3.3, December 2023

5.10, January 2022

23c, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL v3

Open Source

Apache version 2

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

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

Erlang

C++ and CUDA

C and C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Android
BSD
Linux
OS X
Solaris
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

CLI Client
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

View functions in JavaScript

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

improved architecture with release 2.0

Sharding

Round robin

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Multi-source replication
Source-replica replication

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

yes

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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