DBMS > ArcadeDB vs. Hawkular Metrics vs. SwayDB vs. TimescaleDB vs. Tkrzw

System Properties Comparison ArcadeDB vs. Hawkular Metrics vs. SwayDB vs. TimescaleDB vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Secondary database models

Relational DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

Technical documentation

docs.arcadedb.com

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

docs.timescale.com

Developer

Arcade Data

Community supported by Red Hat

Simer Plaha

Timescale

Mikio Hirabayashi

Initial release

2021

2014

2018

2017

2020

Current release

September 2021

2.13.0, November 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GNU Affero GPL V3.0

Open Source

Apache 2.0

Open Source

Apache Version 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

Scala

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Linux
macOS

Data scheme

schema-free

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

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

HTTP REST

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

Supported programming languages

Java

Go
Java
Python
Ruby

Java
Kotlin
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C++
Java
Python
Ruby

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

Triggers

yes

via Hawkular Alerting

yes

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

Source-replica replication

selectable replication factor

based on Cassandra

none

Source-replica replication with hot standby and reads on replicas

none

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

relationship in graphs

yes

Transaction concepts

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

ACID

Atomic execution of operations

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

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