DBMS > BigObject vs. Datomic vs. Ehcache vs. Realm

System Properties Comparison BigObject vs. Datomic vs. Ehcache vs. Realm

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A widely adopted Java cache with tiered storage options

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store

Document store

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

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

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

Technical documentation

docs.bigobject.io

docs.datomic.com

www.ehcache.org/documentation

realm.io/docs

Developer

BigObject, Inc.

Cognitect

Terracotta Inc, owned by Software AG

Realm, acquired by MongoDB in May 2019

Initial release

2015

2012

2009

2014

Current release

1.0.6735, June 2023

3.10.0, March 2022

License

Commercial or Open Source

commercial

free community edition available

commercial

limited edition free

Open Source

Apache Version 2; commercial licenses 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, Clojure

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Android
Backend: server-less
iOS
Windows

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

RESTful HTTP API

JCache

Supported programming languages

Clojure
Java

Java

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

Lua

yes

Transaction Functions

runs within the applications so server-side scripts are unnecessary

Triggers

By using transaction functions

yes

Cache Event Listeners

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

by using Terracotta Server

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

by using Terracotta Server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

using a tiered cache-storage approach

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

In-Memory realm

User concepts

Access control

yes

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