DBMS > LeanXcale vs. OrientDB vs. Postgres-XL vs. SWC-DB

System Properties Comparison LeanXcale vs. OrientDB vs. Postgres-XL vs. SWC-DB

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

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A high performance, scalable Wide Column DBMS

Primary database model

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Wide column store

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

www.leanxcale.com

orientdb.org

www.postgres-xl.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

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

www.postgres-xl.org/documentation

Developer

LeanXcale

OrientDB LTD; CallidusCloud; SAP

Alex Kashirin

Initial release

2015

2010

2014

since 2012, originally named StormDB

2020

Current release

3.2.29, March 2024

10 R1, October 2018

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Mozilla public license

Open Source

GPL V3

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

C++

Server operating systems

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

Linux
macOS

Linux

Data scheme

yes

schema-free

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

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

SQL-like query language, no joins

yes

distributed, parallel query execution

SQL-like query language

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Proprietary protocol
Thrift

Supported programming languages

C
Java
Scala

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++

Server-side scripts

Stored procedures

Java, Javascript

user defined functions

Triggers

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Transaction concepts

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

ACID

MVCC

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

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard

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

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

OrientDB: A Flexible and Scalable Multi-Model NoSQL DBMS
21 January 2022, Open Source For You

Comparing Graph Databases II. Part 2: ArangoDB, OrientDB, and… | by Sam Bell
20 September 2019, Towards Data Science

The 12 Best Graph Databases to Consider for 2024
22 October 2023, Solutions Review

ArangoDB raises $10 million for NoSQL database management
14 March 2019, VentureBeat

Introducing Gremlin The Graph Database
14 August 2013, iProgrammer

provided by Google News

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News

Share this page