DBMS > Google BigQuery vs. Oracle Rdb vs. RDF4J vs. ScyllaDB

System Properties Comparison Google BigQuery vs. Oracle Rdb vs. RDF4J vs. ScyllaDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

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

Cassandra and DynamoDB compatible wide column store

Primary database model

Relational DBMS

RDF store

Wide column store

Secondary database models

Key-value store

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Website

cloud.google.com/bigquery

www.oracle.com/database/technologies/related/rdb.html

rdf4j.org

www.scylladb.com

Technical documentation

cloud.google.com/bigquery/docs

www.oracle.com/database/technologies/related/rdb-doc.html

rdf4j.org/documentation

docs.scylladb.com

Developer

Google

Oracle, originally developed by Digital Equipment Corporation (DEC)

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

ScyllaDB

Initial release

2010

1984

2004

2015

Current release

7.4.1.1, 2021

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Open Source (AGPL), commercial license available

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.

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Implementation language

Java

C++

Server operating systems

hosted

HP Open VMS

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

RDF Schemas

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.

Secondary indexes

yes

cluster global secondary indices

SQL

Support of SQL

yes

SQL-like DML and DDL statements (CQL)

APIs and other access methods

RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
PHP
Python

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

yes, Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

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

yes, on a single node

ACID

Isolation support depends on the API used

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

in-memory tables

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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