DBMS > Google BigQuery vs. TerminusDB vs. Trafodion vs. VelocityDB

System Properties Comparison Google BigQuery vs. TerminusDB vs. Trafodion vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Transactional SQL-on-Hadoop DBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
RDF store

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

cloud.google.com/bigquery

terminusdb.com

trafodion.apache.org

velocitydb.com

Technical documentation

cloud.google.com/bigquery/docs

terminusdb.github.io/terminusdb/#

trafodion.apache.org/documentation.html

velocitydb.com/UserGuide

Developer

Google

DataChemist Ltd.

Apache Software Foundation, originally developed by HP

VelocityDB Inc

Initial release

2010

2018

2014

2011

Current release

11.0.0, January 2023

2.3.0, February 2019

7.x

License

Commercial or Open Source

commercial

Open Source

GPL V3

Open Source

Apache 2.0

commercial

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

Prolog, Rust

C++, Java

Server operating systems

hosted

Linux

Any that supports .NET

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

yes

APIs and other access methods

RESTful HTTP/JSON API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

ADO.NET
JDBC
ODBC

.Net

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript
Python

All languages supporting JDBC/ODBC/ADO.Net

.Net

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Java Stored Procedures

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Journaling Streams

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Role-based access control

fine grained access rights according to SQL-standard

Based on Windows Authentication

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