DBMS > Hazelcast vs. Stardog vs. Tkrzw vs. VoltDB

System Properties Comparison Hazelcast vs. Stardog vs. Tkrzw vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

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	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

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

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

Technical documentation

hazelcast.org/imdg/docs

docs.stardog.com

docs.voltdb.com

Developer

Hazelcast

Stardog-Union

Mikio Hirabayashi

VoltDB Inc.

Initial release

2008

2010

2020

2010

Current release

5.3.6, November 2023

7.3.0, May 2020

0.9.3, August 2020

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache Version 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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, C++

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

Linux
macOS

Linux
OS X

for development

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

SQL-like query language

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

only a subset of SQL 99

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C++
Java
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions and aggregates, HTTP Server extensions in Java

Java

Triggers

yes

Events

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication in HA-Cluster

none

Multi-source replication
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 or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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 for users and roles

Users and roles with access to stored procedures

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