DBMS > AllegroGraph vs. Faircom DB vs. Microsoft Azure Cosmos DB vs. Sadas Engine vs. Teradata

System Properties Comparison AllegroGraph vs. Faircom DB vs. Microsoft Azure Cosmos DB vs. Sadas Engine vs. Teradata

Editorial information provided by DB-Engines

Name

Description

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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Globally distributed, horizontally scalable, multi-model database service

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series 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	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

allegrograph.com

www.faircom.com/products/faircom-db

azure.microsoft.com/services/cosmos-db

www.sadasengine.com

www.teradata.com

Technical documentation

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

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

learn.microsoft.com/azure/cosmos-db

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.teradata.com

Developer

Franz Inc.

FairCom Corporation

Microsoft

SADAS s.r.l.

Teradata

Initial release

2004

1979

2014

2006

1984

Current release

8.0, December 2023

V12, November 2020

8.0

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Restricted, free version available

commercial

free trial version available

commercial

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

ANSI C, C++

C++

Server operating systems

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

hosted

AIX
Linux
Windows

hosted
Linux

Data scheme

yes

RDF schemas

schema free, schema optional, schema required, partial schema,

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

JSON 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

Secondary indexes

yes

All properties auto-indexed by default

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SPARQL is used as query language

yes, ANSI SQL with proprietary extensions

SQL-like query language

yes

SQL 2016 + extensions

APIs and other access methods

RESTful HTTP API
SPARQL

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC
Proprietary protocol

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

.Net, JavaScript, C/C++

JavaScript

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

Implicit feature of the cloud service

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

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

Fine grained access rights according to SQL-standard with additional protections for files

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

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...
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Competitive advantages

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

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