DBMS > Coveo vs. LeanXcale vs. mSQL vs. OrientDB

System Properties Comparison Coveo vs. LeanXcale vs. mSQL vs. OrientDB

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Editorial information provided by DB-Engines

Name

Description

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Primary database model

Search engine

Key-value store
Relational DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

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

Score	2.28
Rank	#114	Overall
	#11	Search engines

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Website

www.coveo.com

www.leanxcale.com

hughestech.com.au/products/msql

orientdb.org

Technical documentation

docs.coveo.com

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

Developer

Coveo

LeanXcale

Hughes Technologies

OrientDB LTD; CallidusCloud; SAP

Initial release

2012

2015

1994

2010

Current release

4.4, October 2021

3.2.29, March 2024

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Apache version 2

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

Java

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language, no joins

APIs and other access methods

RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC

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

Supported programming languages

C#
Java
JavaScript
Python

C
Java
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

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

Server-side scripts

Stored procedures

Java, Javascript

Triggers

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

none

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

yes

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

granular access controls, API key management, content filters

Access rights for users and roles; record level security configurable

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