DBMS > GeoSpock vs. Hawkular Metrics vs. RDF4J vs. TimescaleDB vs. YottaDB

System Properties Comparison GeoSpock vs. Hawkular Metrics vs. RDF4J vs. TimescaleDB vs. YottaDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

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

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

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

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Time Series DBMS

Relational DBMS

using the Octo plugin

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

geospock.com

Technical documentation

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

rdf4j.org/documentation

docs.timescale.com

yottadb.com/resources/documentation

Developer

GeoSpock

Community supported by Red Hat

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

Timescale

YottaDB, LLC

Initial release

2014

2004

2017

2001

Current release

2.0, September 2019

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache 2.0

Open Source

AGPL 3.0

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, Javascript

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Docker
Linux

Data scheme

yes

schema-free

yes

RDF Schemas

yes

schema-free

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

full PostgreSQL SQL syntax

by using the Octo plugin

APIs and other access methods

JDBC

HTTP REST

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

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

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Go
Java
Python
Ruby

Java
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

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

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

based on Cassandra

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Source-replica replication with hot standby and reads on replicas

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

ACID

Isolation support depends on the API used

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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 can be defined per table

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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More resources

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