DBMS > Dgraph vs. Google BigQuery vs. MarkLogic vs. SwayDB

System Properties Comparison Dgraph vs. Google BigQuery vs. MarkLogic vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Large scale data warehouse service with append-only tables

Operational and transactional Enterprise NoSQL database

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Graph DBMS

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Key-value store

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

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	4.15
Rank	#70	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#8	Search engines

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Website

dgraph.io

cloud.google.com/bigquery

www.progress.com/marklogic

swaydb.simer.au

Technical documentation

dgraph.io/docs

cloud.google.com/bigquery/docs

www.progress.com/marklogic/documentation

Developer

Dgraph Labs, Inc.

Google

MarkLogic Corp.

Simer Plaha

Initial release

2016

2010

2001

2018

Current release

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

GNU Affero GPL V3.0

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

C++

Scala

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

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

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Java
Kotlin
Scala

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

yes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

none

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

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

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

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Planned for future releases

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

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