DBMS > AllegroGraph vs. Microsoft Azure Data Explorer vs. Oracle vs. Postgres-XL vs. VoltDB

System Properties Comparison AllegroGraph vs. Microsoft Azure Data Explorer vs. Oracle vs. Postgres-XL vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

Fully managed big data interactive analytics platform

Widely used RDBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

column oriented

Relational DBMS

Secondary database models

Spatial DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
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	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

allegrograph.com

azure.microsoft.com/services/data-explorer

www.oracle.com/database

www.postgres-xl.org

www.voltdb.com

Technical documentation

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

docs.microsoft.com/en-us/azure/data-explorer

docs.oracle.com/en/database

www.postgres-xl.org/documentation

docs.voltdb.com

Developer

Franz Inc.

Microsoft

Oracle

VoltDB Inc.

Initial release

2004

2019

1980

2014

since 2012, originally named StormDB

2010

Current release

8.0, December 2023

cloud service with continuous releases

23c, September 2023

10 R1, October 2018

11.3, April 2022

License

Commercial or Open Source

commercial

Limited community edition free

commercial

restricted free version is available

Open Source

Mozilla public license

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

Java, C++

Server operating systems

Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
macOS

Linux
OS X

for development

Data scheme

yes

RDF schemas

Fixed schema with schema-less datatypes (dynamic)

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

XML type, but no XML query functionality

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SPARQL is used as query language

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

yes

distributed, parallel query execution

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API
SPARQL

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Yes, possible languages: KQL, Python, R

PL/SQL

also stored procedures in Java possible

user defined functions

Java

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

MVCC

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

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

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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.