DBMS > Atos Standard Common Repository vs. Google Cloud Firestore vs. Hawkular Metrics vs. SpaceTime

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Firestore vs. Hawkular Metrics vs. SpaceTime

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Google Cloud Firestore  Xexclude from comparison	Hawkular Metrics  Xexclude from comparison	SpaceTime  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	Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.	Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.	SpaceTime is a spatio-temporal DBMS with a focus on performance.
Primary database model	Document store Key-value store	Document store	Time Series DBMS	Spatial DBMS
Secondary database models				Relational DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 7.36 Rank #53   Overall #9   Document stores	Score 0.08 Rank #366   Overall #39   Time Series DBMS	Score 0.03 Rank #392   Overall #8   Spatial DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	firebase.google.com/­products/­firestore	www.hawkular.org	www.mireo.com/­spacetime
Technical documentation		firebase.google.com/­docs/­firestore	www.hawkular.org/­hawkular-metrics/­docs/­user-guide
Developer	Atos Convergence Creators	Google	Community supported by Red Hat	Mireo
Initial release	2016	2017	2014	2020
Current release	1703
License Commercial or Open Source	commercial	commercial	Open Source Apache 2.0	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		Java	C++
Server operating systems	Linux	hosted	Linux OS X Windows	Linux
Data scheme	Schema and schema-less with LDAP views	schema-free	schema-free	yes
Typing predefined data types such as float or date	optional	yes	yes	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	no	no
SQL Support of SQL	no	no	no	A subset of ANSI SQL is implemented
APIs and other access methods	LDAP	Android gRPC (using protocol buffers) API iOS JavaScript API RESTful HTTP API	HTTP REST	RESTful HTTP API
Supported programming languages	All languages with LDAP bindings	Go Java JavaScript JavaScript (Node.js) Objective-C Python	Go Java Python Ruby	C# C++ Python
Server-side scripts Stored procedures	no	yes, Firebase Rules & Cloud Functions	no	no
Triggers	yes	yes, with Cloud Functions	yes via Hawkular Alerting	no
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding	Sharding based on Cassandra	Fixed-grid hypercubes
Replication methods Methods for redundantly storing data on multiple nodes	yes	Multi-source replication	selectable replication factor based on Cassandra	Real-time block device replication (DRBD)
MapReduce Offers an API for user-defined Map/Reduce methods		Using Cloud Dataflow	no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra	Immediate Consistency
Foreign keys Referential integrity	no	no	no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	yes	no	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		no	no
User concepts Access control	LDAP bind authentication	Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.	no	yes
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More resources
	Atos Standard Common Repository	Google Cloud Firestore	Hawkular Metrics	SpaceTime
DB-Engines blog posts		Cloud-based DBMS's popularity grows at high rates 12 December 2019, Paul Andlinger show all
Recent citations in the news		Google's AI-First Strategy Brings Vector Support To Cloud Databases 1 March 2024, Forbes Realtime vs Cloud Firestore: Which Firebase Database to go? 8 March 2024, Appinventiv Google launches Cloud Firestore, a new document database for app developers 3 October 2017, TechCrunch Google's Cloud-Native NoSQL Database Cloud Firestore Is Now Generally Available 8 February 2019, InfoQ.com Firestore and Python | NoSQL on Google Cloud 7 August 2020, Towards Data Science provided by Google News	Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS 5 June 2019, DevClass provided by Google News

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