DBMS > LeanXcale vs. OpenQM vs. RRDtool vs. StarRocks

System Properties Comparison LeanXcale vs. OpenQM vs. RRDtool vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

QpenQM is a high-performance, self-tuning, multi-value DBMS

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.

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Key-value store
Relational DBMS

Multivalue DBMS

Time Series DBMS

Relational DBMS

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

www.leanxcale.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

oss.oetiker.ch/rrdtool

www.starrocks.io

Technical documentation

oss.oetiker.ch/rrdtool/doc

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

LeanXcale

Rocket Software, originally Martin Phillips

Tobias Oetiker

The Linux Foundation

since Feb 2023

Initial release

2015

1993

1999

2020

Current release

3.4-12

1.8.0, 2022

2.5.3, March 2023

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

GPL V2 and FLOSS

Open Source

Apache Version 2.0

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

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

C++, Java

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

HP-UX
Linux

Linux

Data scheme

yes

with some exceptions

yes

Typing

predefined data types such as float or date

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

in-process shared library
Pipes

JDBC
MySQL protocol

Supported programming languages

C
Java
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

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

Java

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

by using the rrdcached daemon

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

User concepts

Access control

Access rights can be defined down to the item level

Role based access control and fine grained access rights

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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