DBMS > Faircom DB vs. InfinityDB vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. Sequoiadb

System Properties Comparison Faircom DB vs. InfinityDB vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

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

A Java embedded Key-Value Store which extends the Java Map interface

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Globally distributed, horizontally scalable, multi-model database service

NewSQL database with distributed OLTP and SQL

Primary database model

Key-value store
Relational DBMS

Key-value store

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

www.faircom.com/products/faircom-db

boilerbay.com

janusgraph.org

azure.microsoft.com/services/cosmos-db

www.sequoiadb.com

Technical documentation

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

boilerbay.com/infinitydb/manual

docs.janusgraph.org

learn.microsoft.com/azure/cosmos-db

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

Developer

FairCom Corporation

Boiler Bay Inc.

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Sequoiadb Ltd.

Initial release

1979

2002

2017

2014

2013

Current release

V12, November 2020

4.0

0.6.3, February 2023

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache 2.0

commercial

Open Source

Server: AGPL; Client: Apache V2

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

ANSI C, C++

Java

C++

Server operating systems

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

easily portable to other OSs

All OS with a Java VM

Linux
OS X
Unix
Windows

hosted

Linux

Data scheme

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

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

JSON types

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

manual creation possible, using inversions based on multi-value capability

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

SQL-like query language

APIs and other access methods

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

proprietary protocol using JSON

Supported programming languages

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

Java

Clojure
Java
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

yes

Implicit feature of the cloud service

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

Relationships in graphs

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

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

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

simple password-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.