DBMS > BigObject vs. EsgynDB vs. Netezza vs. Realm vs. ToroDB

System Properties Comparison BigObject vs. EsgynDB vs. Netezza vs. Realm vs. ToroDB

Editorial information provided by DB-Engines

Name

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

Description

Analytic DBMS for real-time computations and queries

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Data warehouse and analytics appliance part of IBM PureSystems

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

bigobject.io

www.esgyn.cn

www.ibm.com/products/netezza

realm.io

github.com/torodb/server

Technical documentation

docs.bigobject.io

realm.io/docs

Developer

BigObject, Inc.

Esgyn

IBM

Realm, acquired by MongoDB in May 2019

8Kdata

Initial release

2015

2000

2014

2016

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

AGPL-V3

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

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)

Linux

included in appliance

Android
Backend: server-less
iOS
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
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

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

yes

Access rights for users and roles

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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