DBMS > Hawkular Metrics vs. HBase vs. JaguarDB vs. KairosDB vs. ToroDB

System Properties Comparison Hawkular Metrics vs. HBase vs. JaguarDB vs. KairosDB vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB 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.

Wide-column store based on Apache Hadoop and on concepts of BigTable

Performant, highly scalable DBMS for AI and IoT applications

Distributed Time Series DBMS based on Cassandra or H2

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Time Series DBMS

Wide column store

Key-value store
Vector DBMS

Time Series DBMS

Document store

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Website

www.hawkular.org

hbase.apache.org

www.jaguardb.com

github.com/kairosdb/kairosdb

github.com/torodb/server

Technical documentation

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

hbase.apache.org/book.html

www.jaguardb.com/support.html

kairosdb.github.io

Developer

Community supported by Red Hat

Apache Software Foundation

Apache top-level project, originally developed by Powerset

DataJaguar, Inc.

8Kdata

Initial release

2014

2008

2015

2013

2016

Current release

2.3.4, January 2021

3.3 July 2023

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

GPL V3.0

Open Source

Apache 2.0

Open Source

AGPL-V3

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++

the server part. Clients available in other languages

Java

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

using Cygwin

Linux

Linux
OS X
Windows

All OS with a Java 7 VM

Data scheme

schema-free

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

HTTP REST

Java API
RESTful HTTP API
Thrift

JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

Go
Java
Python
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

Multi-source replication

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Single row ACID (across millions of columns)

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

rights management via user accounts

simple password-based access control

Access rights for users and roles

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More resources

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