DBMS > AllegroGraph vs. Apache Kylin vs. Drizzle vs. PouchDB vs. SQLite

System Properties Comparison AllegroGraph vs. Apache Kylin vs. Drizzle vs. PouchDB vs. SQLite

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

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

kylin.apache.org/docs

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

Franz Inc.

Apache Software Foundation, originally contributed from eBay Inc

Drizzle project, originally started by Brian Aker

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2004

2015

2008

2012

2000

Current release

8.0, December 2023

3.1.0, July 2020

7.2.4, September 2012

7.1.1, June 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache Version 2.0

Open Source

GNU GPL

Open Source

Public Domain

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

Java

C++

JavaScript

Server operating systems

Linux
OS X
Windows

Linux

FreeBSD
Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

server-less

Data scheme

yes

RDF schemas

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

via views

yes

SQL

Support of SQL

SPARQL is used as query language

ANSI SQL for queries (using Apache Calcite)

yes

with proprietary extensions

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
ODBC
RESTful HTTP API

JDBC

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C++
Java
PHP

JavaScript

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

View functions in JavaScript

Triggers

yes

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

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

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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

How a Neuro-Symbolic AI Approach Can Improve Trust in AI Apps
23 May 2024

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

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.