DBMS > EJDB vs. Hazelcast vs. LeanXcale vs. Oracle Berkeley DB

System Properties Comparison EJDB vs. Hazelcast vs. LeanXcale vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A widely adopted in-memory data grid

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

Widely used in-process key-value store

Primary database model

Document store

Key-value store

Key-value store
Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

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

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Website

github.com/Softmotions/ejdb

hazelcast.com

www.leanxcale.com

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

hazelcast.org/imdg/docs

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Softmotions

Hazelcast

LeanXcale

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2012

2008

2015

1994

Current release

5.3.6, November 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

commercial license available

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, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

server-less

All OS with a Java VM

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

through Apache Derby

yes

SQL interfaced based on SQLite is available

APIs and other access methods

in-process shared library

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

C
Java
Scala

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Triggers

yes

Events

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Replicated Map

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

typically not needed, however similar functionality with collection joins possible

yes

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

Read/Write Locking

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

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