DBMS > RDF4J vs. Snowflake vs. Teradata vs. Trino

System Properties Comparison RDF4J vs. Snowflake vs. Teradata vs. Trino

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Editorial information provided by DB-Engines

Name

Description

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

RDF store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

Technical documentation

rdf4j.org/documentation

docs.snowflake.net/manuals/index.html

docs.teradata.com

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Snowflake Computing Inc.

Teradata

Trino Software Foundation

Initial release

2004

2014

1984

2012

2020 rebranded from PrestoSQL

Current release

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

Java

Server operating systems

Linux
OS X
Unix
Windows

hosted

hosted
Linux

Linux
macOS

for devlopment

Data scheme

yes

RDF Schemas

yes

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

yes

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

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

depending on connected data-source

SQL

Support of SQL

yes

SQL 2016 + extensions

yes

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

CLI Client
JDBC
ODBC

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

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

Java
PHP
Python

JavaScript (Node.js)
Python

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

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes

UDFs, stored procedures, table functions in parallel

yes, depending on connected data-source

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

Hashing

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

depending on connected data-source

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

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
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Key customers

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Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

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News

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