DBMS > OpenQM vs. OpenTSDB vs. PlanetScale vs. RDF4J

System Properties Comparison OpenQM vs. OpenTSDB vs. PlanetScale vs. RDF4J

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Scalable Time Series DBMS based on HBase

Scalable, distributed, serverless MySQL database platform built on top of Vitess

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

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

opentsdb.net

planetscale.com

rdf4j.org

Technical documentation

opentsdb.net/docs/build/html/index.html

planetscale.com/docs

rdf4j.org/documentation

Developer

Rocket Software, originally Martin Phillips

currently maintained by Yahoo and other contributors

PlanetScale

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

1993

2011

2020

2004

Current release

3.4-12

License

Commercial or Open Source

Open Source

GPLv2, extended commercial license available

Open Source

LGPL

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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.

Implementation language

Java

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
Windows

Docker
Linux
macOS

Linux
OS X
Unix
Windows

Data scheme

yes

with some exceptions

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

numeric data for metrics, strings for tags

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

HTTP API
Telnet API

ADO.NET
JDBC
MySQL protocol
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

Erlang
Go
Java
Python
R
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

based on HBase

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

Users with fine-grained authorization concept

no user groups or roles

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.

Related products and services

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

More resources

DB-Engines blog posts

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

show all

Recent citations in the news

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

MakeMyTrip travels forward in time using the power of open source
16 May 2017, Open Source For You

MapR-DB NoSQL Database Integrated into the MapR Distribution
17 October 2014, insideBIGDATA

provided by Google News

PlanetScale ends free tier bid, sheds staff in profitability bid
11 March 2024, The Register

PlanetScale forks MySQL to add vector support
3 October 2023, TechCrunch

PlanetScale Ranked Number 188 Fastest-Growing Company in North America on the 2023 Deloitte Technology Fast ...
8 November 2023, Yahoo Finance

PlanetScale Named to Fortune 2023 Best Small Workplaces
31 August 2023, Business Wire

Top 70+ startups in Database as a Service (DBaaS)
5 April 2024, Tracxn

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
13 June 2019, Markets Insider

provided by Google News

Share this page