DBMS > ArangoDB vs. BigchainDB vs. NSDb vs. Oracle NoSQL

System Properties Comparison ArangoDB vs. BigchainDB vs. NSDb vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Document store
Graph DBMS
Key-value store
Search engine

Document store

Time Series DBMS

Document store
Key-value store
Relational DBMS

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

Score	3.32
Rank	#90	Overall
	#15	Document stores
	#5	Graph DBMS
	#12	Key-value stores
	#10	Search engines

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

arangodb.com

www.bigchaindb.com

nsdb.io

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

docs.arangodb.com

bigchaindb.readthedocs.io/en/latest

nsdb.io/Architecture

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Social network pages

Developer

ArangoDB Inc.

Oracle

Initial release

2012

2016

2017

2011

Current release

3.11.5, November 2023

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial license (Enterprise) available

Open Source

AGPL v3

Open Source

Apache Version 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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.

ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.

Implementation language

C++

Python

Java, Scala

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
macOS

Linux
Solaris SPARC/x86

Data scheme

schema-free

automatically recognizes schema within a collection

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

yes: int, bigint, decimal, string

optional

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream

CLI Client
RESTful HTTP API

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust

Go
Haskell
Java
JavaScript
Python
Ruby

Java
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with configurable replication factor

selectable replication factor

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

can be done with stored procedures in JavaScript

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

configurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

Using Apache Lucene

yes

In-memory capabilities

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

yes

off heap cache

User concepts

Access control

yes

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more

Competitive advantages

Consolidation: As a native multi-model database, can be used as a full blown document...
» more

Typical application scenarios

Native multi-model in ArangoDB is being used for a broad range of projects across...
» more

Key customers

Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more

Market metrics

ArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more

Licensing and pricing models

Very permissive Apache 2 License for Community Edition & commercial licenses are...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

The Weight of Relational Databases: Time for Multi-Model?
29 August 2017, Luca Olivari (guest author)

show all

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