DBMS > Google BigQuery vs. MarkLogic vs. NSDb vs. RDFox

System Properties Comparison Google BigQuery vs. MarkLogic vs. NSDb vs. RDFox

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Operational and transactional Enterprise NoSQL database

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Time Series DBMS

Graph DBMS
RDF store

Secondary database models

Relational DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Website

cloud.google.com/bigquery

www.progress.com/marklogic

nsdb.io

www.oxfordsemantic.tech

Technical documentation

cloud.google.com/bigquery/docs

www.progress.com/marklogic/documentation

nsdb.io/Architecture

docs.oxfordsemantic.tech

Developer

Google

MarkLogic Corp.

Oxford Semantic Technologies

Initial release

2010

2001

2017

Current release

11.0, December 2022

6.0, Septermber 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 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

C++

Java, Scala

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS

Linux
macOS
Windows

Data scheme

yes

schema-free

Schema can be enforced

yes

RDF schemas

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, 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.

yes

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

SQL92

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

gRPC
HTTP REST
WebSocket

RESTful HTTP API
SPARQL 1.1

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Java
Scala

C
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

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

can act as a resource manager in an XA/JTA transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

In-memory capabilities

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

yes, with Range Indexes

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 at the document and subdocument levels

Roles, resources, and access types

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