DBMS > AnzoGraph DB vs. FatDB vs. Firebase Realtime Database vs. RocksDB vs. TypeDB

System Properties Comparison AnzoGraph DB vs. FatDB vs. Firebase Realtime Database vs. RocksDB vs. TypeDB

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.

Description

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

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Document store

Key-value store

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

cambridgesemantics.com/anzograph

firebase.google.com/products/realtime-database

rocksdb.org

typedb.com

Technical documentation

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

firebase.google.com/docs/database

github.com/facebook/rocksdb/wiki

typedb.com/docs

Developer

Cambridge Semantics

FatCloud

Google

acquired by Google 2014

Facebook, Inc.

Vaticle

Initial release

2018

2012

2013

2016

Current release

2.3, January 2021

9.2.1, May 2024

2.26.3, January 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

BSD

Open Source

GPL Version 3, commercial licenses available

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

C++

Java

Server operating systems

Linux

Windows

hosted

Linux

Linux
OS X
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

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

APIs and other access methods

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

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

Android
iOS
JavaScript API
RESTful HTTP API

C++ API
Java API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

C++
Java
Python

Java
JavaScript
Objective-C

C
C++
Go
Java
Perl
Python
Ruby

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

via applications

limited functionality with using 'rules'

Triggers

yes

via applications

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency
Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

substituted by the relationship feature

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

Can implement custom security layer via applications

yes, based on authentication and database rules

yes

at REST API level; other APIs in progress

More information provided by the system vendor

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