DBMS > BigObject vs. OrientDB vs. RavenDB

System Properties Comparison BigObject vs. OrientDB vs. RavenDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Multi-model DBMS (Document, Graph, Key/Value)

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store
Graph DBMS
Key-value store

Document store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

bigobject.io

orientdb.org

ravendb.net

Technical documentation

docs.bigobject.io

www.orientdb.com/docs/last/index.html

ravendb.net/docs

Developer

BigObject, Inc.

OrientDB LTD; CallidusCloud; SAP

Hibernating Rhinos

Initial release

2015

2010

Current release

3.2.29, March 2024

5.4, July 2022

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache version 2

Open Source

AGPL version 3, commercial license 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

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java JDK (>= JDK 6)

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

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

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language, no joins

SQL-like query language (RQL)

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

Java, Javascript

yes

Triggers

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

relationship in graphs

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles; record level security configurable

Authorization levels configured per client per database

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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Recent citations in the news

The 12 Best Graph Databases to Consider for 2024
22 October 2023, Solutions Review

OrientDB: A Flexible and Scalable Multi-Model NoSQL DBMS
21 January 2022, Open Source For You

Comparing Graph Databases II. Part 2: ArangoDB, OrientDB, and… | by Sam Bell
20 September 2019, Towards Data Science

Mining Botnet Targeting Redis and OrientDB Servers Made Almost $1 Million
2 February 2018, BleepingComputer

ArangoDB raises $10 million for NoSQL database management
14 March 2019, VentureBeat

provided by Google News

RavenDB Launches Version 6.0 Lightning Fast Queries, Data Integrations, Corax Indexing Engine, and Sharding
3 October 2023, PR Newswire

RavenDB Welcomes David Baruc as Chief Revenue Officer: Seasoned Tech Leader to Drive Global Sales and ...
13 June 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

How I Created a RavenDB Python Client
23 September 2016, Visual Studio Magazine

RavenDB Adds Graph Queries
15 May 2019, Datanami

provided by Google News

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