DBMS > AnzoGraph DB vs. Datomic vs. FatDB vs. VelocityDB vs. Yaacomo

System Properties Comparison AnzoGraph DB vs. Datomic vs. FatDB vs. VelocityDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Key-value store

Graph DBMS
Object oriented DBMS

Relational DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

cambridgesemantics.com/anzograph

www.datomic.com

velocitydb.com

yaacomo.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.datomic.com

velocitydb.com/UserGuide

Developer

Cambridge Semantics

Cognitect

FatCloud

VelocityDB Inc

Q2WEB GmbH

Initial release

2018

2012

2011

2009

Current release

2.3, January 2021

1.0.6735, June 2023

7.x

License

Commercial or Open Source

commercial

free trial version available

commercial

limited edition free

commercial

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, Clojure

Server operating systems

Linux

All OS with a Java VM

Windows

Any that supports .NET

Android
Linux
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

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

SPARQL and SPARQL* as primary query language. Cypher preview.

Via inetgration in SQL Server

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

.Net

JDBC
ODBC

Supported programming languages

C++
Java
Python

Clojure
Java

.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Transaction Functions

yes

via applications

Triggers

By using transaction functions

yes

via applications

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

But extensive use of caching in the application peers

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

But extensive use of caching in the application peers

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users and roles

Can implement custom security layer via applications

Based on Windows Authentication

fine grained access rights according to SQL-standard

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More resources

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