DBMS > Faircom DB vs. JanusGraph vs. Memgraph vs. NSDb

System Properties Comparison Faircom DB vs. JanusGraph vs. Memgraph vs. NSDb

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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 Graph DBMS optimized for distributed clusters

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

An open source graph database built for real-time streaming and compatible with Neo4j

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Key-value store
Relational DBMS

Graph DBMS

Time Series DBMS

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

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

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.faircom.com/products/faircom-db

janusgraph.org

memgraph.com

nsdb.io

Technical documentation

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

docs.janusgraph.org

memgraph.com/docs

nsdb.io/Architecture

Social network pages

Developer

FairCom Corporation

Linux Foundation; originally developed as Titan by Aurelius

Memgraph Ltd

Initial release

1979

2017

Current release

V12, November 2020

0.6.3, February 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

BSL 1.1; commercial license for enterprise edition available

Open Source

Apache Version 2.0

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++

Java

C and C++

Java, Scala

Server operating systems

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

easily portable to other OSs

Linux
OS X
Unix
Windows

Linux

Linux
macOS

Data scheme

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

yes

schema-free and schema-optional

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Bolt protocol
Cypher query language

gRPC
HTTP REST
WebSocket

Supported programming languages

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

Clojure
Java
Python

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

Java
Scala

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

yes

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

Sharding

dynamic graph partitioning

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).

yes

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationships in graphs

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

with periodic snapshot and write-ahead logging (WAL) of changes

Using Apache Lucene

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

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
» more

Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
» more

Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more

Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

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