DBMS > Hawkular Metrics vs. Memcached vs. SQLite vs. TimescaleDB vs. UniData,UniVerse

System Properties Comparison Hawkular Metrics vs. Memcached vs. SQLite vs. TimescaleDB vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

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

In-memory key-value store, originally intended for caching

Widely used embeddable, in-process RDBMS

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

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Relational DBMS

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

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	20.74
Rank	#32	Overall
	#4	Key-value stores

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Score	3.47
Rank	#93	Overall
	#2	Multivalue DBMS

Website

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

Technical documentation

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

github.com/memcached/memcached/wiki

www.sqlite.org/docs.html

docs.timescale.com

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Community supported by Red Hat

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Dwayne Richard Hipp

Timescale

Rocket Software

Initial release

2014

2003

2000

2017

1985

Current release

1.6.25, March 2024

3.45.3 (15 April 2024), April 2024

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD license

Open Source

Public Domain

Open Source

Apache 2.0

commercial

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

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Unix
Windows

server-less

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

dynamic column types

yes

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

optional

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

SQL-92 is not fully supported

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

HTTP REST

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Go
Java
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

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

yes

Triggers

yes

via Hawkular Alerting

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Repcached, a Memcached patch, provides this functionallity

none

Source-replica replication with hot standby and reads on replicas

Source-replica replication

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

Access rights according to SQL-standard and operating system based

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.