DBMS > Atos Standard Common Repository vs. Hawkular Metrics vs. JaguarDB vs. RRDtool vs. Snowflake

System Properties Comparison Atos Standard Common Repository vs. Hawkular Metrics vs. JaguarDB vs. RRDtool vs. Snowflake

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Performant, highly scalable DBMS for AI and IoT applications

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Key-value store

Time Series DBMS

Key-value store
Vector DBMS

Time Series DBMS

Relational DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.hawkular.org

www.jaguardb.com

oss.oetiker.ch/rrdtool

www.snowflake.com

Technical documentation

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

www.jaguardb.com/support.html

oss.oetiker.ch/rrdtool/doc

docs.snowflake.net/manuals/index.html

Developer

Atos Convergence Creators

Community supported by Red Hat

DataJaguar, Inc.

Tobias Oetiker

Snowflake Computing Inc.

Initial release

2016

2014

2015

1999

2014

Current release

1703

3.3 July 2023

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL V3.0

Open Source

GPL V2 and FLOSS

commercial

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

C++

the server part. Clients available in other languages

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux

Linux
OS X
Windows

Linux

HP-UX
Linux

hosted

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

optional

yes

Numeric data only

yes

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

Exporting into and restoring from XML files possible

yes

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

LDAP

HTTP REST

JDBC
ODBC

in-process shared library
Pipes

CLI Client
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

Go
Java
Python
Ruby

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

via Hawkular Alerting

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on Cassandra

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

LDAP bind authentication

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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