DBMS > Ehcache vs. OrigoDB vs. RavenDB vs. Realm vs. Riak TS

System Properties Comparison Ehcache vs. OrigoDB vs. RavenDB vs. Realm vs. Riak TS

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

A fully ACID in-memory object graph database

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Key-value store

Document store
Object oriented DBMS

Document store

Time Series DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

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

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

Technical documentation

www.ehcache.org/documentation

origodb.com/docs

ravendb.net/docs

realm.io/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Terracotta Inc, owned by Software AG

Robert Friberg et al

Hibernating Rhinos

Realm, acquired by MongoDB in May 2019

Open Source, formerly Basho Technologies

Initial release

2009

under the name LiveDB

2010

2014

2015

Current release

3.10.0, March 2022

5.4, July 2022

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

AGPL version 3, commercial license available

Open Source

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

Erlang

Server operating systems

All OS with a Java VM

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Android
Backend: server-less
iOS
Windows

Linux
OS X

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like query language (RQL)

yes, limited

APIs and other access methods

JCache

.NET Client API
HTTP API
LINQ

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

Java

.Net

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Java

with Android only
Objective-C
React Native
Swift

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

runs within the applications so server-side scripts are unnecessary

Erlang

Triggers

yes

Cache Event Listeners

yes

Domain Events

yes

Change Listeners

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

horizontal partitioning

client side managed; servers are not synchronized

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Source-replica replication

Multi-source replication

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

depending on model

links between datasets can be stored

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

In-Memory realm

User concepts

Access control

Role based authorization

Authorization levels configured per client per database

yes

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More resources

DB-Engines blog posts

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