DBMS > Graph Engine vs. Stardog vs. Teradata vs. Yanza

System Properties Comparison Graph Engine vs. Stardog vs. Teradata vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A hybrid cloud data analytics software platform (Teradata Vantage)

Time Series DBMS for IoT Applications

Primary database model

Graph DBMS
Key-value store

Graph DBMS
RDF store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Website

www.graphengine.io

www.stardog.com

www.teradata.com

yanza.com

Technical documentation

www.graphengine.io/docs/manual

docs.stardog.com

docs.teradata.com

Developer

Microsoft

Stardog-Union

Teradata

Yanza

Initial release

2010

1984

2015

Current release

7.3.0, May 2020

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

MIT License

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

.NET and C

Java

Server operating systems

.NET

Linux
macOS
Windows

hosted
Linux

Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

yes

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

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

SQL

Support of SQL

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

SQL 2016 + extensions

APIs and other access methods

RESTful HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

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

HTTP API

Supported programming languages

C#
C++
F#
Visual Basic

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions and aggregates, HTTP Server extensions in Java

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

via event handlers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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2 April 2013, Paul Andlinger

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