DBMS > GraphDB vs. Hypertable vs. mSQL vs. Snowflake vs. XTDB

System Properties Comparison GraphDB vs. Hypertable vs. mSQL vs. Snowflake vs. XTDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

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.

An open source BigTable implementation based on distributed file systems such as Hadoop

mSQL (Mini SQL) is a simple and lightweight RDBMS

Cloud-based data warehousing service for structured and semi-structured data

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

Primary database model

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	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.ontotext.com

hughestech.com.au/products/msql

www.snowflake.com

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

Technical documentation

graphdb.ontotext.com/documentation

docs.snowflake.net/manuals/index.html

www.xtdb.com/docs

Social network pages

Developer

Ontotext

Hypertable Inc.

Hughes Technologies

Snowflake Computing Inc.

Juxt Ltd.

Initial release

2000

2009

1994

2014

2019

Current release

10.4, October 2023

0.9.8.11, March 2016

4.4, October 2021

1.19, September 2021

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

GNU version 3. Commercial license available

commercial

free licenses can be provided

commercial

Open Source

MIT License

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

Java

C++

Clojure

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

Linux
OS X
Windows

an inofficial Windows port is available

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

hosted

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

Data scheme

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

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

limited SQL, making use of Apache Calcite

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

C++ API
Thrift

JDBC
ODBC

CLI Client
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

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

C++
Java
Perl
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

JavaScript (Node.js)
Python

Clojure
Java

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor on file system level

none

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Foreign keys

Referential integrity

yes

Constraint checking

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

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.

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.

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

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.