DBMS > AllegroGraph vs. Datomic vs. Hazelcast vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server

System Properties Comparison AllegroGraph vs. Datomic vs. Hazelcast vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

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

A widely adopted in-memory data grid

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Microsofts flagship relational DBMS

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS
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	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

allegrograph.com

www.datomic.com

hazelcast.com

azure.microsoft.com/services/synapse-analytics

www.microsoft.com/en-us/sql-server

Technical documentation

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

docs.datomic.com

hazelcast.org/imdg/docs

docs.microsoft.com/azure/synapse-analytics

learn.microsoft.com/en-US/sql/sql-server

Developer

Franz Inc.

Cognitect

Hazelcast

Microsoft

Initial release

2004

2012

2008

2016

1989

Current release

8.0, December 2023

1.0.6735, June 2023

5.3.6, November 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Limited community edition free

commercial

limited edition free

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

hosted

Linux
Windows

Data scheme

yes

RDF schemas

yes

schema-free

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

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API
SPARQL

RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

Clojure
Java

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C#
Java
PHP

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

Transaction Functions

yes

Event Listeners, Executor Services

Transact SQL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

By using transaction functions

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

But extensive use of caching in the application peers

Sharding

Sharding, horizontal partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

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

yes

Replicated Map

yes

yes, but depending on the SQL-Server Edition

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

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

Role-based access control

yes

fine grained access rights according to SQL-standard

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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