DBMS > EJDB vs. Hazelcast vs. Microsoft Azure Cosmos DB vs. Tkrzw

System Properties Comparison EJDB vs. Hazelcast vs. Microsoft Azure Cosmos DB vs. Tkrzw

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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

Globally distributed, horizontally scalable, multi-model database service

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

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

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	5.72
Rank	#59	Overall
	#6	Key-value stores

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

github.com/Softmotions/ejdb

hazelcast.com

azure.microsoft.com/services/cosmos-db

dbmx.net/tkrzw

Technical documentation

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

hazelcast.org/imdg/docs

learn.microsoft.com/azure/cosmos-db

Developer

Softmotions

Hazelcast

Microsoft

Mikio Hirabayashi

Initial release

2012

2008

2014

2020

Current release

5.3.6, November 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

server-less

All OS with a Java VM

hosted

Linux
macOS

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

APIs and other access methods

in-process shared library

JCache
JPA
Memcached protocol
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

JavaScript

Triggers

yes

Events

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Replicated Map

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

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

Multi-item ACID transactions with snapshot isolation within a partition

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

using specific database classes

User concepts

Access control

Role-based access control

Access rights can be defined down to the item level

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