DBMS > GraphDB vs. Microsoft SQL Server vs. Splice Machine vs. TinkerGraph vs. Warp 10

System Properties Comparison GraphDB vs. Microsoft SQL Server vs. Splice Machine vs. TinkerGraph vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Microsofts flagship relational DBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	3.32
Rank	#91	Overall
	#6	Graph DBMS
	#4	RDF stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.ontotext.com

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

splicemachine.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

www.warp10.io

Technical documentation

graphdb.ontotext.com/documentation

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

splicemachine.com/how-it-works

www.warp10.io/content/02_Getting_started

Social network pages

Developer

Ontotext

Microsoft

Splice Machine

SenX

Initial release

2000

1989

2014

2009

2015

Current release

10.4, October 2023

SQL Server 2022, November 2022

3.1, March 2021

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

restricted free version is available

Open Source

AGPL 3.0, commercial license available

Open Source

Apache 2.0

Open Source

Apache License 2.0

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++

Java

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

Linux
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free and OWL/RDFS-schema support; RDF shapes

yes

schema-free

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.

yes

Secondary indexes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

APIs and other access methods

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

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

JDBC
Native Spark Datasource
ODBC

TinkerPop 3

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Groovy
Java

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

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

yes

Java

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Immediate Consistency

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Constraint checking

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional

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

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

fine grained access rights according to SQL-standard

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

Migrating From LPG to RDF Graph Model
8 May 2024

Case study: Policy Enforcement Automation With Semantics
2 May 2024

Okay, RAG… We Have a Problem
26 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.