DBMS > Google BigQuery vs. jBASE vs. RDF4J vs. ReductStore

System Properties Comparison Google BigQuery vs. jBASE vs. RDF4J vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A robust multi-value DBMS comprising development tools and middleware

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

cloud.google.com/bigquery

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

rdf4j.org

github.com/reductstore
www.reduct.store

Technical documentation

cloud.google.com/bigquery/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

rdf4j.org/documentation

www.reduct.store/docs

Developer

Google

Rocket Software (formerly Zumasys)

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

ReductStore LLC

Initial release

2010

1991

2004

2023

Current release

5.7

1.9, March 2024

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Business Source License 1.1

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, Rust

Server operating systems

hosted

AIX
Linux
Windows

Linux
OS X
Unix
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

yes

Embedded SQL for jBASE in BASIC

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Basic
Jabbascript
Java

Java
PHP
Python

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

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)

Access rights can be defined down to the item level

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