DBMS > Oracle Coherence vs. Realm vs. Transwarp Hippo vs. VoltDB

System Properties Comparison Oracle Coherence vs. Realm vs. Transwarp Hippo vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Oracles in-memory data grid solution

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

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

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

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

www.oracle.com/java/coherence

realm.io

www.transwarp.cn/en/subproduct/hippo

www.voltdb.com

Technical documentation

docs.oracle.com/en/middleware/standalone/coherence

realm.io/docs

docs.voltdb.com

Developer

Oracle

Realm, acquired by MongoDB in May 2019

VoltDB Inc.

Initial release

2007

2014

2023

2010

Current release

14.1, August 2023

1.0, May 2023

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

commercial

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

Android
Backend: server-less
iOS
Windows

Linux
macOS

Linux
OS X

for development

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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.

Secondary indexes

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

JCache
JPA
RESTful HTTP API

RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C++
Java

.Net
Java

with Android only
Objective-C
React Native
Swift

C++
Java
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

Java

Triggers

yes

Live Events

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with selectable consistency level

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

configurable

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

optionally

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

In-Memory realm

yes

User concepts

Access control

authentification to access the cache via certificates or http basic authentication

yes

Role based access control and fine grained access rights

Users and roles with access to stored procedures

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More resources

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