DBMS > atoti vs. IBM Cloudant vs. RavenDB vs. VelocityDB

System Properties Comparison atoti vs. IBM Cloudant vs. RavenDB vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Database as a Service offering based on Apache CouchDB

Open Source Operational and Transactional Enterprise NoSQL Document Database

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Object oriented DBMS

Document store

Graph DBMS
Object oriented DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

atoti.io

www.ibm.com/products/cloudant

ravendb.net

velocitydb.com

Technical documentation

docs.atoti.io

cloud.ibm.com/docs/Cloudant

ravendb.net/docs

velocitydb.com/UserGuide

Developer

ActiveViam

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Hibernating Rhinos

VelocityDB Inc

Initial release

2010

2011

Current release

5.4, July 2022

7.x

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

AGPL version 3, commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

Server operating systems

hosted

Linux
macOS
Raspberry Pi
Windows

Any that supports .NET

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.

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language (RQL)

APIs and other access methods

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

.Net

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

.Net

Server-side scripts

Stored procedures

Python

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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.

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Optimistic locking

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 can be defined per database

Authorization levels configured per client per database

Based on Windows Authentication

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