DBMS > LeanXcale vs. MonetDB vs. OrientDB

System Properties Comparison LeanXcale vs. MonetDB vs. OrientDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A relational database management system that stores data in columns

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	0.17
Rank	#297	Overall
	#43	Key-value stores
	#138	Relational DBMS

Score	1.80
Rank	#131	Overall
	#64	Relational DBMS

Score	4.86
Rank	#80	Overall
	#14	Document stores
	#5	Graph DBMS
	#12	Key-value stores

Website

www.leanxcale.com

www.monetdb.org

orientdb.org

Technical documentation

www.monetdb.org/Documentation

www.orientdb.com/docs/last/index.html

Developer

LeanXcale

MonetDB BV

OrientDB LTD; CallidusCloud; SAP

Initial release

2015

2004

2010

Current release

Jul2021-SP2, July 2021

3.1.9, February 2021

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache version 2

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

Java

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

SQL

Support of SQL

yes

through Apache Derby

yes

SQL 2003 with some extensions

SQL-like query language, no joins

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

C
Java
Scala

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes, in SQL, C, R

Java, Javascript

Triggers

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

More information provided by the system vendor

Specific characteristics

Full ACID and full SQL operational database with analytical queries over operational...
» more

Column-store In-memory optimized GeoSpatial support JSON document support
» more

Competitive advantages

Linear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
» more

Scalable architecture - vertical data organization and in-memory optimization guarantee...
» more

Typical application scenarios

Hybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
» more

Analytical database, Data warehouse, OLAP Data mining Scientific database
» more

Key customers

banking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
» more

Numascale , Spinque , SecurActive , CHS , NOZHUP
» more

Market metrics

15 beta testers
» more

Licensing and pricing models

annual fee covering license and support based on number of physical cores
» more

Free and open-source software, Mozilla Public License 2.0 Commercial support available
» more

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

DB-Engines blog posts