DBMS > Atos Standard Common Repository vs. Galaxybase vs. Google Cloud Datastore vs. Hawkular Metrics

System Properties Comparison Atos Standard Common Repository vs. Galaxybase vs. Google Cloud Datastore vs. Hawkular Metrics

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Galaxybase  Xexclude from comparison	Google Cloud Datastore  Xexclude from comparison	Hawkular Metrics  Xexclude from comparison
	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	Scalable, ACID-compliant native distributed parallel graph platform	Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform	Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database model	Document store Key-value store	Graph DBMS	Document store	Time Series DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.07 Rank #377   Overall #40   Graph DBMS	Score 4.36 Rank #72   Overall #12   Document stores	Score 0.08 Rank #366   Overall #39   Time Series DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	galaxybase.com	cloud.google.com/­datastore	www.hawkular.org
Technical documentation			cloud.google.com/­datastore/­docs	www.hawkular.org/­hawkular-metrics/­docs/­user-guide
Developer	Atos Convergence Creators	Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司	Google	Community supported by Red Hat
Initial release	2016	2017	2008	2014
Current release	1703	Nov 20, November 2021
License Commercial or Open Source	commercial	commercial	commercial	Open Source Apache 2.0
Cloud-based only Only available as a cloud service	no	no	yes	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	C and Java		Java
Server operating systems	Linux	Linux	hosted	Linux OS X Windows
Data scheme	Schema and schema-less with LDAP views	Strong typed schema	schema-free	schema-free
Typing predefined data types such as float or date	optional	yes	yes, details here	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	no	no	no
Secondary indexes	yes	yes	yes	no
SQL Support of SQL	no	no	SQL-like query language (GQL)	no
APIs and other access methods	LDAP	Browser interface console (shell) Graph API (Gremlin) OpenCypher Proprietary native API	gRPC (using protocol buffers) API RESTful HTTP/JSON API	HTTP REST
Supported programming languages	All languages with LDAP bindings	Go Java Python	.Net Go Java JavaScript (Node.js) PHP Python Ruby	Go Java Python Ruby
Server-side scripts Stored procedures	no	user defined procedures and functions	using Google App Engine	no
Triggers	yes		Callbacks using the Google Apps Engine	yes via Hawkular Alerting
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding	Sharding	Sharding based on Cassandra
Replication methods Methods for redundantly storing data on multiple nodes	yes		Multi-source replication using Paxos	selectable replication factor based on Cassandra
MapReduce Offers an API for user-defined Map/Reduce methods		no	yes using Google Cloud Dataflow	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Immediate Consistency or Eventual Consistency depending on type of query and configuration Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra
Foreign keys Referential integrity	no	yes Relationships in graphs	yes via ReferenceProperties or Ancestor paths	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	ACID	ACID Serializable Isolation within Transactions, Read Committed outside of Transactions	no
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	yes	no	no
User concepts Access control	LDAP bind authentication	Role-based access control	Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)	no
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More resources
	Atos Standard Common Repository	Galaxybase	Google Cloud Datastore	Hawkular Metrics
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