DBMS > EJDB vs. Hazelcast vs. SQream DB vs. Tkrzw

System Properties Comparison EJDB vs. Hazelcast vs. SQream 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

a GPU-based, columnar RDBMS for big data analytics workloads

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

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	0.74
Rank	#224	Overall
	#103	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

github.com/Softmotions/ejdb

hazelcast.com

sqream.com

dbmx.net/tkrzw

Technical documentation

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

hazelcast.org/imdg/docs

docs.sqream.com

Developer

Softmotions

Hazelcast

SQream Technologies

Mikio Hirabayashi

Initial release

2012

2008

2017

2020

Current release

5.3.6, November 2023

2022.1.6, December 2022

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

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, CUDA, Haskell, Java, Scala

C++

Server operating systems

server-less

All OS with a Java VM

Linux

Linux
macOS

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

yes, ANSI Standard SQL 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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

in-process shared library

JCache
JPA
Memcached protocol
RESTful HTTP API

.Net
JDBC
ODBC

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
JavaScript (Node.js)
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions in Python

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Replicated Map

none

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

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

using specific database classes

User concepts

Access control

Role-based access control

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