DBMS > Hazelcast vs. InfinityDB vs. KeyDB vs. RDF4J

System Properties Comparison Hazelcast vs. InfinityDB vs. KeyDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

A Java embedded Key-Value Store which extends the Java Map interface

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Key-value store

RDF store

Secondary database models

Document store

JSON support with IMDG 3.12

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

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

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

hazelcast.com

boilerbay.com

github.com/Snapchat/KeyDB
keydb.dev

rdf4j.org

Technical documentation

hazelcast.org/imdg/docs

boilerbay.com/infinitydb/manual

docs.keydb.dev

rdf4j.org/documentation

Developer

Hazelcast

Boiler Bay Inc.

EQ Alpha Technology Ltd.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2008

2002

2019

2004

Current release

5.3.6, November 2023

4.0

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

BSD-3

Open Source

Eclipse Distribution License (EDL), v1.0.

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++

Java

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

by using the Redis Search module

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Proprietary protocol

RESP - REdis Serialization Protoco

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

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

Java

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Lua

yes

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

none

Multi-source replication
Source-replica replication

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

READ-COMMITTED or SERIALIZED

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

in-memory storage is supported as well

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

simple password-based access control and ACL

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