DBMS > AllegroGraph vs. atoti vs. Microsoft SQL Server vs. Qdrant vs. SwayDB

System Properties Comparison AllegroGraph vs. atoti vs. Microsoft SQL Server vs. Qdrant vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Microsofts flagship relational DBMS

A high-performance vector database with neural network or semantic-based matching

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
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	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

allegrograph.com

atoti.io

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

github.com/qdrant/qdrant
qdrant.tech

swaydb.simer.au

Technical documentation

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

docs.atoti.io

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

qdrant.tech/documentation

Developer

Franz Inc.

ActiveViam

Microsoft

Qdrant

Simer Plaha

Initial release

2004

1989

2021

2018

Current release

8.0, December 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Limited community edition free

commercial

free versions available

commercial

restricted free version is available

Open Source

Apache Version 2.0

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Rust

Scala

Server operating systems

Linux
OS X
Windows

Linux
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

RDF schemas

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SPARQL is used as query language

Multidimensional Expressions (MDX)

yes

APIs and other access methods

RESTful HTTP API
SPARQL

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Python

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding, horizontal partitioning

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Collection-level replication

none

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

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Key-based authentication

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

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23 May 2024

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17 April 2024

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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

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