DBMS > EXASOL vs. Google BigQuery vs. Hyprcubd vs. RDF4J vs. TinkerGraph

System Properties Comparison EXASOL vs. Google BigQuery vs. Hyprcubd vs. RDF4J vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Large scale data warehouse service with append-only tables

Serverless Time Series DBMS

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

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

Primary database model

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

www.exasol.com

cloud.google.com/bigquery

hyprcubd.com (offline)

rdf4j.org

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

Technical documentation

www.exasol.com/resources

cloud.google.com/bigquery/docs

rdf4j.org/documentation

Developer

Exasol

Google

Hyprcubd, Inc.

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

Initial release

2000

2010

2004

2009

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache 2.0

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

Server operating systems

hosted

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

gRPC (https)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

TinkerPop 3

Supported programming languages

Java
Lua
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
PHP
Python

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

optional

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, groups and roles according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

token access

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