DBMS > Hawkular Metrics vs. Microsoft Azure Table Storage vs. OrigoDB vs. Yaacomo

System Properties Comparison Hawkular Metrics vs. Microsoft Azure Table Storage vs. OrigoDB vs. Yaacomo

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Editorial information provided by DB-Engines
Name	Hawkular Metrics  Xexclude from comparison	Microsoft Azure Table Storage  Xexclude from comparison	OrigoDB  Xexclude from comparison	Yaacomo  Xexclude from comparison
				Yaacomo seems to be discontinued and is removed 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.	A Wide Column Store for rapid development using massive semi-structured datasets	A fully ACID in-memory object graph database	OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database model	Time Series DBMS	Wide column store	Document store Object oriented 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 4.04 Rank #77   Overall #6   Wide column stores	Score 0.06 Rank #380   Overall #50   Document stores #18   Object oriented DBMS
Website	www.hawkular.org	azure.microsoft.com/­en-us/­services/­storage/­tables	origodb.com	yaacomo.com
Technical documentation	www.hawkular.org/­hawkular-metrics/­docs/­user-guide		origodb.com/­docs
Developer	Community supported by Red Hat	Microsoft	Robert Friberg et al	Q2WEB GmbH
Initial release	2014	2012	2009 under the name LiveDB	2009
License Commercial or Open Source	Open Source Apache 2.0	commercial	Open Source	commercial
Cloud-based only Only available as a cloud service	no	yes	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java		C#
Server operating systems	Linux OS X Windows	hosted	Linux Windows	Android Linux Windows
Data scheme	schema-free	schema-free	yes	yes
Typing predefined data types such as float or date	yes	yes	User defined using .NET types and collections	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.	no	no	no can be achieved using .NET	no
Secondary indexes	no	no	yes	yes
SQL Support of SQL	no	no	no	yes
APIs and other access methods	HTTP REST	RESTful HTTP API	.NET Client API HTTP API LINQ	JDBC ODBC
Supported programming languages	Go Java Python Ruby	.Net C# C++ Java JavaScript (Node.js) PHP Python Ruby	.Net
Server-side scripts Stored procedures	no	no	yes
Triggers	yes via Hawkular Alerting	no	yes Domain Events	yes
Partitioning methods Methods for storing different data on different nodes	Sharding based on Cassandra	Sharding Implicit feature of the cloud service	horizontal partitioning client side managed; servers are not synchronized	horizontal partitioning
Replication methods Methods for redundantly storing data on multiple nodes	selectable replication factor based on Cassandra	yes implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.	Source-replica replication	Source-replica replication
MapReduce Offers an API for user-defined Map/Reduce methods	no	no	no	no
Consistency concepts Methods to ensure consistency in a distributed system	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra	Immediate Consistency		Immediate Consistency
Foreign keys Referential integrity	no	no	depending on model	yes
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	no	optimistic locking	ACID	ACID
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes Write ahead log	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	no	no	yes	yes
User concepts Access control	no	Access rights based on private key authentication or shared access signatures	Role based authorization	fine grained access rights according to SQL-standard
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More resources
	Hawkular Metrics	Microsoft Azure Table Storage	OrigoDB	Yaacomo
Recent citations in the news	Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS 5 June 2019, DevClass provided by Google News	Working with Azure to Use and Manage Data Lakes 7 March 2024, Simplilearn How to use Azure Table storage in .Net 14 January 2019, InfoWorld How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB 9 July 2021, hackernoon.com Inside Azure File Storage 7 October 2015, Microsoft How to write data to Azure Table Store with an Azure Function 14 April 2017, Experts Exchange provided by Google News

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