DBMS > Hive vs. OpenQM vs. RocksDB vs. RRDtool

System Properties Comparison Hive vs. OpenQM vs. RocksDB vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

hive.apache.org

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

rocksdb.org

oss.oetiker.ch/rrdtool

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

github.com/facebook/rocksdb/wiki

oss.oetiker.ch/rrdtool/doc

Developer

Apache Software Foundation

initially developed by Facebook

Rocket Software, originally Martin Phillips

Facebook, Inc.

Tobias Oetiker

Initial release

2012

1993

2013

1999

Current release

3.1.3, April 2022

3.4-12

9.2.1, May 2024

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPLv2, extended commercial license available

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.

Implementation language

Java

C++

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

Server operating systems

All OS with a Java VM

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

HP-UX
Linux

Data scheme

yes

with some exceptions

schema-free

yes

Typing

predefined data types such as float or date

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
Thrift

C++ API
Java API

in-process shared library
Pipes

Supported programming languages

C++
Java
PHP
Python

.Net
Basic
C
Java
Objective C
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

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

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

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

Access rights for users, groups and roles

Access rights can be defined down to the item level

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