DBMS > BigObject vs. Ehcache vs. IRONdb vs. Oracle Rdb

System Properties Comparison BigObject vs. Ehcache vs. IRONdb vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for real-time computations and queries

A widely adopted Java cache with tiered storage options

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Time Series DBMS

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

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

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

bigobject.io

www.ehcache.org

www.circonus.com/solutions/time-series-database/

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

docs.bigobject.io

www.ehcache.org/documentation

docs.circonus.com/irondb/category/getting-started

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

BigObject, Inc.

Terracotta Inc, owned by Software AG

Circonus LLC.

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2015

2009

2017

1984

Current release

3.10.0, March 2022

V0.10.20, January 2018

7.4.1.1, 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available

commercial

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 and C++

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

Linux

HP Open VMS

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JCache

HTTP API

Supported programming languages

Java

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

Lua

yes, in Lua

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

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

User concepts

Access control

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