DBMS > IRONdb vs. Oracle vs. Realm vs. Splice Machine vs. STSdb

System Properties Comparison IRONdb vs. Oracle vs. Realm vs. Splice Machine vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph

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

Score	0.00
Rank	#354	Overall
	#33	Time Series DBMS

Score	1262.82
Rank	#1	Overall
	#1	Relational DBMS

Score	9.89
Rank	#49	Overall
	#8	Document stores

Score	0.80
Rank	#193	Overall
	#91	Relational DBMS

Score	0.01
Rank	#345	Overall
	#53	Key-value stores

Website

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

www.oracle.com/database

realm.io

splicemachine.com

github.com/STSSoft/STSdb4

Technical documentation

docs.circonus.com/irondb

docs.oracle.com/en/database

realm.io/docs

doc.splicemachine.com

Developer

Circonus LLC.

Oracle

Realm, acquired by MongoDB in May 2019

Splice Machine

STS Soft SC

Initial release

2017

1980

2014

2011

Current release

V0.10.20, January 2018

19c, February 2019

3.1, March 2021

4.0.8, September 2015

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

AGPL 3.0, commercial license available

Open Source

GPLv2, commercial license available

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

C and C++

Java

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Android
Backend: server-less
iOS
Windows

Linux
OS X
Solaris
Windows

Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

primitive types and user defined types (classes)

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

Secondary indexes

yes

SQL

Support of SQL

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

yes

with proprietary extensions

yes

APIs and other access methods

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
Native Spark Datasource
ODBC

.NET Client API

Supported programming languages

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

yes, in Lua

PL/SQL

also stored procedures in Java possible

runs within the applications so server-side scripts are unnecessary

yes

Java

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding, horizontal partitioning

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

Now a part of MongoDB Data Platform , Realm Database is the fast, easy to use, and...
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Competitive advantages

Realm ensures offline-first functionality, meaning apps run smoothly and deliver...
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Typical application scenarios

Mobile Consumer Apps First-Line Worker Apps
» more

Key customers

Cathay Pacific Royal Carribbean Cruise Lines Open Source Database powers apps built...
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Market metrics

Used by 100,000+ developers 2 bn installs Currently used in 40k+ applications in...
» more

Licensing and pricing models

Realm database is licensed under the Apache License v2.0.
» more

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