DBMS > Faircom DB vs. Memgraph vs. SQLite vs. XTDB

System Properties Comparison Faircom DB vs. Memgraph vs. SQLite vs. XTDB

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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.

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

Widely used embeddable, in-process RDBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Relational DBMS

Graph DBMS

Relational DBMS

Document store

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	3.19
Rank	#94	Overall
	#8	Graph DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.faircom.com/products/faircom-db

memgraph.com

www.sqlite.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

memgraph.com/docs

www.sqlite.org/docs.html

www.xtdb.com/docs

Social network pages

Developer

FairCom Corporation

Memgraph Ltd

Dwayne Richard Hipp

Juxt Ltd.

Initial release

1979

2017

2000

2019

Current release

V12, November 2020

3.46.0 (23 May 2024), May 2024

1.19, September 2021

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

BSL 1.1; commercial license for enterprise edition available

Open Source

Public Domain

Open Source

MIT License

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

ANSI C, C++

C and C++

Clojure

Server operating systems

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

easily portable to other OSs

Linux

server-less

All OS with a Java 8 (and higher) VM
Linux

Data scheme

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

schema-free and schema-optional

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

not rigid because of 'dynamic typing' concept.

yes, extensible-data-notation format

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

yes, ANSI SQL with proprietary extensions

yes

SQL-92 is not fully supported

limited SQL, making use of Apache Calcite

APIs and other access methods

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

Bolt protocol
Cypher query language

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

HTTP REST
JDBC

Supported programming languages

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

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Clojure
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

dynamic graph partitioning

none

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).

Multi-source replication using RAFT

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

yes

Durability

Support for making data persistent

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

yes

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

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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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