DBMS > Hazelcast vs. LeanXcale vs. OrientDB

System Properties Comparison Hazelcast vs. LeanXcale vs. OrientDB

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

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

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

Primary database model

Key-value store

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

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

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

Website

hazelcast.com

www.leanxcale.com

orientdb.org

Technical documentation

hazelcast.org/imdg/docs

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

Developer

Hazelcast

LeanXcale

OrientDB LTD; CallidusCloud; SAP

Initial release

2008

2015

2010

Current release

5.3.6, November 2023

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

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

All OS with a Java VM

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

Data scheme

schema-free

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

through Apache Derby

SQL-like query language, no joins

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

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

Supported programming languages

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

C
Java
Scala

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

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Java, Javascript

Triggers

yes

Events

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

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

Role-based access control

Access rights for users and roles; record level security configurable

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More resources

DB-Engines blog posts

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