DBMS > EsgynDB vs. Machbase Neo vs. Realm vs. ToroDB vs. Transwarp Hippo

System Properties Comparison EsgynDB vs. Machbase Neo vs. Realm vs. ToroDB vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

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

Description

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

TimeSeries DBMS for AIoT and BigData

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Website

www.esgyn.cn

machbase.com

realm.io

github.com/torodb/server

www.transwarp.cn/en/subproduct/hippo

Technical documentation

machbase.com/dbms

realm.io/docs

Developer

Esgyn

Machbase

Realm, acquired by MongoDB in May 2019

8Kdata

Initial release

2015

2013

2014

2016

2023

Current release

V8.0, August 2023

1.0, May 2023

License

Commercial or Open Source

commercial

free test version available

Open Source

AGPL-V3

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

C++, Java

Java

C++

Server operating systems

Linux

Linux
macOS
Windows

Android
Backend: server-less
iOS
Windows

All OS with a Java 7 VM

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

Vector, Numeric and String

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

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

C++
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

volatile and lookup table

yes

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

yes

Access rights for users and roles

Role based access control and fine grained access rights

More information provided by the system vendor

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