DBMS > Hawkular Metrics vs. Hyprcubd vs. Memgraph vs. MySQL vs. TimescaleDB

System Properties Comparison Hawkular Metrics vs. Hyprcubd vs. Memgraph vs. MySQL vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Serverless Time Series DBMS

An open source graph database built for real-time streaming and compatible with Neo4j

Widely used open source RDBMS

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

Primary database model

Time Series DBMS

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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	3.00
Rank	#102	Overall
	#8	Graph DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

www.hawkular.org

hyprcubd.com (offline)

memgraph.com

www.mysql.com

www.timescale.com

Technical documentation

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

memgraph.com/docs

dev.mysql.com/doc

docs.timescale.com

Developer

Community supported by Red Hat

Hyprcubd, Inc.

Memgraph Ltd

Oracle

since 2010, originally MySQL AB, then Sun

Timescale

Initial release

2014

2017

1995

2017

Current release

8.3.0, January 2024

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Free license available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free and schema-optional

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP REST

gRPC (https)

Bolt protocol
Cypher query language

ADO.NET
JDBC
ODBC
Proprietary native API

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

Supported programming languages

Go
Java
Python
Ruby

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

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

Sharding

based on Cassandra

Sharding

dynamic graph partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication using RAFT

Multi-source replication
Source-replica replication

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

with snapshot isolation

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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

token access

Users, roles and permissions

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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