DBMS > Atos Standard Common Repository vs. Fujitsu Enterprise Postgres vs. Heroic vs. Lovefield

System Properties Comparison Atos Standard Common Repository vs. Fujitsu Enterprise Postgres vs. Heroic vs. Lovefield

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Fujitsu Enterprise Postgres  Xexclude from comparison	Heroic  Xexclude from comparison	Lovefield  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	Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.	Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch	Embeddable relational database for web apps written in pure JavaScript
Primary database model	Document store Key-value store	Relational DBMS	Time Series DBMS	Relational DBMS
Secondary database models		Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.37 Rank #278   Overall #128   Relational DBMS	Score 0.46 Rank #265   Overall #22   Time Series DBMS	Score 0.33 Rank #286   Overall #131   Relational DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.postgresql.fastware.com	github.com/­spotify/­heroic	google.github.io/­lovefield
Technical documentation		www.postgresql.fastware.com/­product-manuals	spotify.github.io/­heroic	github.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
Developer	Atos Convergence Creators	PostgreSQL Global Development Group, Fujitsu Australia Software Technology	Spotify	Google
Initial release	2016		2014	2014
Current release	1703	Fujitsu Enterprise Postgres 14, January 2022		2.1.12, February 2017
License Commercial or Open Source	commercial	commercial	Open Source Apache 2.0	Open Source Apache 2.0
Cloud-based only Only available as a cloud service	no	no	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	C	Java	JavaScript
Server operating systems	Linux	Linux Windows		server-less, requires a JavaScript environment (browser, Node.js) tested with Chrome, Firefox, IE, Safari
Data scheme	Schema and schema-less with LDAP views	yes	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
Secondary indexes	yes	yes	yes via Elasticsearch	yes
SQL Support of SQL	no	yes	no	SQL-like query language via JavaScript builder pattern
APIs and other access methods	LDAP	ADO.NET JDBC native C library ODBC streaming API for large objects	HQL (Heroic Query Language, a JSON-based language) HTTP API
Supported programming languages	All languages with LDAP bindings	.Net C C++ Delphi Java JavaScript (Node.js) Perl PHP Python Tcl		JavaScript
Server-side scripts Stored procedures	no	user defined functions	no	no
Triggers	yes	yes	no	Using read-only observers
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	partitioning by range, list and by hash	Sharding	none
Replication methods Methods for redundantly storing data on multiple nodes	yes	Source-replica replication	yes	none
MapReduce Offers an API for user-defined Map/Reduce methods		no	no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Eventual Consistency Immediate Consistency
Foreign keys Referential integrity	no	yes	no	yes
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	ACID	no	ACID
Concurrency Support for concurrent manipulation of data	yes	yes, multi-version concurrency control (MVCC)	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes, by using IndexedDB or the cloud service Firebase Realtime Database
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes		no	yes using MemoryDB
User concepts Access control	LDAP bind authentication	fine grained access rights according to SQL-standard		no
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More resources
	Atos Standard Common Repository	Fujitsu Enterprise Postgres	Heroic	Lovefield
Recent citations in the news		Fujitsu Develops Column-Oriented Data-Processing Engine Enabling Fast, High-Volume Data Analysis in Database ... 26 February 2015, Fujitsu Expert Insight 202009 KAC 4 September 2023, Fujitsu Fujitsu recognized as winner of 2023 Microsoft Japan Healthcare & Life Sciences Partner of the Year Award for its ... 28 June 2023, Fujitsu Primary Data says stop, Hammerspace, Innodisk cooks some SSDs, and Fujitsu goes blockchain 22 May 2018, The Register DCPMM 1 August 2020, Fujitsu provided by Google News	Review: Google Bigtable scales with ease 7 September 2016, InfoWorld provided by Google News

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