DBMS > MarkLogic vs. Newts vs. OrigoDB vs. XTDB

System Properties Comparison MarkLogic vs. Newts vs. OrigoDB vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Operational and transactional Enterprise NoSQL database

Time Series DBMS based on Cassandra

A fully ACID in-memory object graph database

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Time Series DBMS

Document store
Object oriented DBMS

Document store

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

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

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.marklogic.com

opennms.github.io/newts

origodb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.marklogic.com

github.com/OpenNMS/newts/wiki

origodb.com/docs

www.xtdb.com/docs

Developer

MarkLogic Corp.

OpenNMS Group

Robert Friberg et al

Juxt Ltd.

Initial release

2001

2014

2009

under the name LiveDB

2019

Current release

11.0, December 2022

1.19, September 2021

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Clojure

Server operating systems

Linux
OS X
Windows

Linux
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

Schema can be enforced

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes, extensible-data-notation format

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

limited SQL, making use of Apache Calcite

APIs and other access methods

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

HTTP REST
Java API

.NET Client API
HTTP API
LINQ

HTTP REST
JDBC

Supported programming languages

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

Java

.Net

Clojure
Java

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Source-replica replication

yes, each node contains all data

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

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

depending on model

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of 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

Write ahead log

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Role-based access control at the document and subdocument levels

Role based authorization

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

MarkLogic “The NoSQL Database”. In the MarkLogic Query Console, you can… | by Abhay Srivastava | Apr, 2024
22 April 2024, Medium

ABN AMRO Moves Progress-Powered Credit Store App to Azure Cloud; Achieves 40% Faster Data Processing, Lower ...
12 March 2024, GlobeNewswire

AI can make logistics data as valuable as intelligence or operational data for mission success
17 April 2024, Breaking Defense

Seven Quick Steps to Setting Up MarkLogic Server in Kubernetes
1 February 2024, release.nl

Progress to acquire PE-backed data platform MarkLogic for $355m
4 January 2023, PE Hub

provided by Google News

Share this page