DBMS > Geode vs. Hawkular Metrics vs. OpenQM vs. RocksDB vs. TimescaleDB

System Properties Comparison Geode vs. Hawkular Metrics vs. OpenQM vs. RocksDB vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Relational DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

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

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

geode.apache.org

www.hawkular.org

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

rocksdb.org

www.timescale.com

Technical documentation

geode.apache.org/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

github.com/facebook/rocksdb/wiki

docs.timescale.com

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Community supported by Red Hat

Rocket Software, originally Martin Phillips

Facebook, Inc.

Timescale

Initial release

2002

2014

1993

2013

2017

Current release

1.1, February 2017

3.4-12

8.11.4, April 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

BSD

Open Source

Apache 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

Java

C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

with some exceptions

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL-like query language (OQL)

yes

full PostgreSQL SQL syntax

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

HTTP REST

C++ API
Java API

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

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

Go
Java
Python
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Cache Event Listeners

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

horizontal partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

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 per client and object definable

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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