DBMS > EsgynDB vs. Hazelcast vs. ITTIA vs. OrigoDB

System Properties Comparison EsgynDB vs. Hazelcast vs. ITTIA vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A widely adopted in-memory data grid

Edge Time Series DBMS with Real-Time Stream Processing

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

Document store
Object oriented DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Relational DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

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

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

Technical documentation

hazelcast.org/imdg/docs

origodb.com/docs

Developer

Esgyn

Hazelcast

ITTIA L.L.C.

Robert Friberg et al

Initial release

2015

2008

2007

2009

under the name LiveDB

Current release

5.3.6, November 2023

8.7

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

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

C++, Java

Java

C and C++

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

Data scheme

yes

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API
WebSocket

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

C
C++
JavaScript (Node.js)
Python

.Net

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Event Listeners, Executor Services

yes

Triggers

yes

Events

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Replicated Map

yes

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Write ahead log

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

Database file passwords

Role based authorization

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