DBMS > AnzoGraph DB vs. Faircom DB vs. RethinkDB vs. Sequoiadb

System Properties Comparison AnzoGraph DB vs. Faircom DB vs. RethinkDB vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

NewSQL database with distributed OLTP and SQL

Primary database model

Graph DBMS
RDF store

Key-value store
Relational DBMS

Document store

Document store
Relational DBMS

Secondary database models

Spatial 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	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.faircom.com/products/faircom-db

rethinkdb.com

www.sequoiadb.com

Technical documentation

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

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

rethinkdb.com/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Cambridge Semantics

FairCom Corporation

The Linux Foundation

since July 2017

Sequoiadb Ltd.

Initial release

2018

1979

2009

2013

Current release

2.3, January 2021

V12, November 2020

2.4.1, August 2020

License

Commercial or Open Source

commercial

free trial version available

commercial

Restricted, free version available

Open Source

Apache Version 2

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

C++

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
OS X
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

schema free, schema optional, schema required, partial schema,

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

string, binary, float, bool, date, geometry

yes

oid, date, timestamp, binary, regex

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.

yes, ANSI SQL with proprietary extensions

SQL-like query language

APIs and other access methods

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

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

proprietary protocol using JSON

Supported programming languages

C++
Java
Python

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

.Net, JavaScript, C/C++

JavaScript

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

range based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

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

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

Atomic single-document operations

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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

Fine grained access rights according to SQL-standard with additional protections for files

yes

users and table-level permissions

simple password-based access control

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More resources

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