DBMS > BigObject vs. Ignite vs. Realm vs. STSdb

System Properties Comparison BigObject vs. Ignite vs. Realm vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store
Relational DBMS

Document store

Key-value store

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

bigobject.io

ignite.apache.org

realm.io

github.com/STSSoft/STSdb4

Technical documentation

docs.bigobject.io

apacheignite.readme.io/docs

realm.io/docs

Developer

BigObject, Inc.

Apache Software Foundation

Realm, acquired by MongoDB in May 2019

STS Soft SC

Initial release

2015

2014

2011

Current release

Apache Ignite 2.6

4.0.8, September 2015

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

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++, Java, .Net

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Solaris
Windows

Android
Backend: server-less
iOS
Windows

Windows

Data scheme

yes

Typing

predefined data types such as float or date

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 DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

.NET Client API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
Java

Server-side scripts

Stored procedures

Lua

yes (compute grid and cache interceptors can be used instead)

runs within the applications so server-side scripts are unnecessary

Triggers

yes (cache interceptors and events)

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

In-Memory realm

User concepts

Access control

Security Hooks for custom implementations

yes

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More resources

DB-Engines blog posts

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