DBMS > EsgynDB vs. eXtremeDB vs. Google BigQuery vs. MarkLogic

System Properties Comparison EsgynDB vs. eXtremeDB vs. Google BigQuery vs. MarkLogic

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Natively in-memory DBMS with options for persistency, high-availability and clustering

Large scale data warehouse service with append-only tables

Operational and transactional Enterprise NoSQL database

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

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

Website

www.esgyn.cn

www.mcobject.com

cloud.google.com/bigquery

www.marklogic.com

Technical documentation

www.mcobject.com/docs/extremedb.htm

cloud.google.com/bigquery/docs

docs.marklogic.com

Developer

Esgyn

McObject

Google

MarkLogic Corp.

Initial release

2015

2001

2010

2001

Current release

8.2, 2021

11.0, December 2022

License

Commercial or Open Source

commercial

restricted free version is 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.

Implementation language

C++, Java

C and C++

C++

Server operating systems

Linux

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

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.

support of XML interfaces available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

SQL92

APIs and other access methods

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful 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

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
Java
Lua
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions

in JavaScript

yes

via XQuery or JavaScript

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning / sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

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

yes

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

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

yes, with Range Indexes

User concepts

Access control

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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