DBMS > EsgynDB vs. KairosDB vs. NuoDB vs. PostgreSQL vs. Transwarp Hippo

System Properties Comparison EsgynDB vs. KairosDB vs. NuoDB vs. PostgreSQL vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Description

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

Distributed Time Series DBMS based on Cassandra or H2

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Vector DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

www.esgyn.cn

github.com/kairosdb/kairosdb

www.3ds.com/nuodb-distributed-sql-database

www.postgresql.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

kairosdb.github.io

doc.nuodb.com

www.postgresql.org/docs

Developer

Esgyn

Dassault Systèmes

originally NuoDB, Inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2015

2013

1989

1989: Postgres, 1996: PostgreSQL

2023

Current release

1.2.2, November 2018

16.3, May 2024

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

limited edition free

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Java

C++

Server operating systems

Linux

Linux
OS X
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript

Node.js
PHP
Python

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

data is dynamically stored/cached on the nodes where it is read/written

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

based on Cassandra

yes

Managed transparently by NuoDB

Source-replica replication

other methods possible by using 3rd party extensions

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

Temporary table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

More information provided by the system vendor

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