DBMS > Derby vs. Hazelcast vs. OrigoDB vs. SWC-DB

System Properties Comparison Derby vs. Hazelcast vs. OrigoDB vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A widely adopted in-memory data grid

A fully ACID in-memory object graph database

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Key-value store

Document store
Object oriented DBMS

Wide column store

Secondary database models

Document store

JSON support with IMDG 3.12

Time Series DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

db.apache.org/derby

hazelcast.com

origodb.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

db.apache.org/derby/manuals/index.html

hazelcast.org/imdg/docs

origodb.com/docs

Developer

Apache Software Foundation

Hazelcast

Robert Friberg et al

Alex Kashirin

Initial release

1997

2008

2009

under the name LiveDB

2020

Current release

10.17.1.0, November 2023

5.3.6, November 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL V3

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++

Server operating systems

All OS with a Java VM

Linux
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

APIs and other access methods

JDBC

JCache
JPA
Memcached protocol
RESTful HTTP API

.NET Client API
HTTP API
LINQ

Proprietary protocol
Thrift

Supported programming languages

Java

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

.Net

C++

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

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

fine grained access rights according to SQL-standard

Role-based access control

Role based authorization

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