DBMS > Heroic vs. openGemini vs. PostgreSQL vs. RRDtool

System Properties Comparison Heroic vs. openGemini vs. PostgreSQL vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

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

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Widely used open source RDBMS

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

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.

Time Series 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	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

github.com/spotify/heroic

www.opengemini.org
github.com/openGemini

www.postgresql.org

oss.oetiker.ch/rrdtool

Technical documentation

spotify.github.io/heroic

docs.opengemini.org/guide

www.postgresql.org/docs

oss.oetiker.ch/rrdtool/doc

Developer

Spotify

Huawei and openGemini community

PostgreSQL Global Development Group

www.postgresql.org/developer

Tobias Oetiker

Initial release

2014

2022

1989

1989: Postgres, 1996: PostgreSQL

1999

Current release

1.1, July 2023

16.3, May 2024

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

GPL V2 and FLOSS

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.

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Implementation language

Java

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux
Windows

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

HP-UX
Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

yes

standard with numerous extensions

APIs and other access methods

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

HTTP REST

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

in-process shared library
Pipes

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

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

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

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

by using the rrdcached daemon

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

User concepts

Access control

Administrators and common users accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

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Related products and services

3rd parties

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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

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more DBMS events

PASS Data Community Summit
Seattle, Washington, 4-8 November 2024

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