DBMS > AllegroGraph vs. LMDB vs. Quasardb vs. SQLite vs. TigerGraph

System Properties Comparison AllegroGraph vs. LMDB vs. Quasardb vs. SQLite vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

A high performant, light-weight, embedded key-value database library

Distributed, high-performance timeseries database

Widely used embeddable, in-process RDBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Secondary database models

Spatial DBMS

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

allegrograph.com

www.symas.com/symas-embedded-database-lmdb

quasar.ai

www.sqlite.org

www.tigergraph.com

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

www.lmdb.tech/doc

doc.quasar.ai/master

www.sqlite.org/docs.html

docs.tigergraph.com

Developer

Franz Inc.

Symas

quasardb

Dwayne Richard Hipp

Initial release

2004

2011

2009

2000

2017

Current release

8.0, December 2023

0.9.32, January 2024

3.14.1, January 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Public Domain

commercial

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

C++

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

BSD
Linux
OS X
Windows

server-less

Linux

Data scheme

yes

RDF schemas

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

integer and binary

yes

not rigid because of 'dynamic typing' concept.

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.

bulk load of XML files possible

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language

yes

SQL-92 is not fully supported

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API
SPARQL

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

C++
Java

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

Cryptographically strong user authentication and audit trail

Role-based access control

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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