DBMS > AllegroGraph vs. Hawkular Metrics vs. Microsoft SQL Server vs. NSDb vs. XTDB

System Properties Comparison AllegroGraph vs. Hawkular Metrics vs. Microsoft SQL Server vs. NSDb vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Microsofts flagship relational DBMS

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A general purpose database with bitemporal SQL and Datalog and graph queries

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	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

allegrograph.com

www.hawkular.org

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

nsdb.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

www.hawkular.org/hawkular-metrics/docs/user-guide

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

nsdb.io/Architecture

www.xtdb.com/docs

Developer

Franz Inc.

Community supported by Red Hat

Microsoft

Juxt Ltd.

Initial release

2004

2014

1989

2017

2019

Current release

8.0, December 2023

SQL Server 2022, November 2022

1.19, September 2021

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache Version 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

Java

C++

Java, Scala

Clojure

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
macOS

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

RDF schemas

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes, extensible-data-notation format

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 fields are automatically indexed

yes

SQL

Support of SQL

SPARQL is used as query language

yes

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API
SPARQL

HTTP REST

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

gRPC
HTTP REST
WebSocket

HTTP REST
JDBC

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

Go
Java
Python
Ruby

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

Java
Scala

Clojure
Java

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

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

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

based on Cassandra

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

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

yes, each node contains all data

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual 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 Apache Lucene

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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

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

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