DBMS > Heroic vs. IBM Cloudant vs. Kingbase vs. PostgreSQL vs. VictoriaMetrics

System Properties Comparison Heroic vs. IBM Cloudant vs. Kingbase vs. PostgreSQL vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Database as a Service offering based on Apache CouchDB

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Widely used open source RDBMS

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Time Series DBMS

Document store

Relational DBMS

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

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

github.com/spotify/heroic

www.ibm.com/products/cloudant

www.kingbase.com.cn

www.postgresql.org

victoriametrics.com

Technical documentation

spotify.github.io/heroic

cloud.ibm.com/docs/Cloudant

www.postgresql.org/docs

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Spotify

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

BeiJing KINGBASE Information technologies inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

VictoriaMetrics

Initial release

2014

2010

1999

1989

1989: Postgres, 1996: PostgreSQL

2018

Current release

V8.0, August 2021

16.3, May 2024

v1.91, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java

Erlang

C and Java

Server operating systems

hosted

Linux
Windows

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

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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

via Elasticsearch

yes

SQL

Support of SQL

Standard with numerous extensions

yes

standard with numerous extensions

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP/JSON API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

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

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

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

horizontal partitioning (by range, list and hash) and vertical partitioning

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

Source-replica replication

other methods possible by using 3rd party extensions

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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