DBMS > Hazelcast vs. Heroic vs. RocksDB vs. UniData,UniVerse

System Properties Comparison Hazelcast vs. Heroic vs. RocksDB vs. UniData,UniVerse

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

MultiValue database and application server with SQL mapping layer and meta database capabilities

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	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	3.47
Rank	#93	Overall
	#2	Multivalue DBMS

Website

hazelcast.com

github.com/spotify/heroic

rocksdb.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

hazelcast.org/imdg/docs

spotify.github.io/heroic

github.com/facebook/rocksdb/wiki

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Hazelcast

Spotify

Facebook, Inc.

Rocket Software

Initial release

2008

2014

2013

1985

Current release

5.3.6, November 2023

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

optional

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

C++ API
Java API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Triggers

yes

Events

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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 or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

yes

ACID

configurable

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

Role-based access control

Access rights according to SQL-standard and operating system based

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