DBMS > AllegroGraph vs. Datomic vs. Drizzle vs. SAP HANA

System Properties Comparison AllegroGraph vs. Datomic vs. Drizzle vs. SAP HANA

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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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

allegrograph.com

www.datomic.com

www.sap.com/products/hana.html

Technical documentation

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

docs.datomic.com

help.sap.com/hana

Developer

Franz Inc.

Cognitect

Drizzle project, originally started by Brian Aker

SAP

Initial release

2004

2012

2008

2010

Current release

8.0, December 2023

1.0.6735, June 2023

7.2.4, September 2012

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Limited community edition free

commercial

limited edition free

Open Source

GNU GPL

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Clojure

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

FreeBSD
Linux
OS X

Appliance or cloud-service

Data scheme

yes

RDF schemas

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SPARQL is used as query language

yes

with proprietary extensions

yes

APIs and other access methods

RESTful HTTP API
SPARQL

RESTful HTTP API

JDBC

JDBC
ODBC

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

Clojure
Java

C
C++
Java
PHP

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

Transaction Functions

SQLScript, R

Triggers

yes

By using transaction functions

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

But extensive use of caching in the application peers

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

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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