DBMS > Atos Standard Common Repository vs. Drizzle vs. InfinityDB vs. JanusGraph

System Properties Comparison Atos Standard Common Repository vs. Drizzle vs. InfinityDB vs. JanusGraph

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Drizzle  Xexclude from comparison	InfinityDB  Xexclude from comparison	JanusGraph successor of Titan  Xexclude from comparison
	This system has been discontinued and will be removed from the DB-Engines ranking.	Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
Description	Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks	MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.	A Java embedded Key-Value Store which extends the Java Map interface	A Graph DBMS optimized for distributed clusters It was forked from the latest code base of Titan in January 2017
Primary database model	Document store Key-value store	Relational DBMS	Key-value store	Graph DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart			Score 0.08 Rank #365   Overall #55   Key-value stores	Score 2.02 Rank #125   Overall #12   Graph DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository		boilerbay.com	janusgraph.org
Technical documentation			boilerbay.com/­infinitydb/­manual	docs.janusgraph.org
Developer	Atos Convergence Creators	Drizzle project, originally started by Brian Aker	Boiler Bay Inc.	Linux Foundation; originally developed as Titan by Aurelius
Initial release	2016	2008	2002	2017
Current release	1703	7.2.4, September 2012	4.0	0.6.3, February 2023
License Commercial or Open Source	commercial	Open Source GNU GPL	commercial	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	Java
Server operating systems	Linux	FreeBSD Linux OS X	All OS with a Java VM	Linux OS X Unix Windows
Data scheme	Schema and schema-less with LDAP views	yes	yes nested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgrade	yes
Typing predefined data types such as float or date	optional	yes	yes all Java primitives, Date, CLOB, BLOB, huge sparse arrays	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	no manual creation possible, using inversions based on multi-value capability	yes
SQL Support of SQL	no	yes with proprietary extensions	no	no
APIs and other access methods	LDAP	JDBC	Access via java.util.concurrent.ConcurrentNavigableMap Interface Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)	Java API TinkerPop Blueprints TinkerPop Frames TinkerPop Gremlin TinkerPop Rexster
Supported programming languages	All languages with LDAP bindings	C C++ Java PHP	Java	Clojure Java Python
Server-side scripts Stored procedures	no	no	no	yes
Triggers	yes	no hooks for callbacks inside the server can be used.	no	yes
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding	none	yes depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)
Replication methods Methods for redundantly storing data on multiple nodes	yes	Multi-source replication Source-replica replication	none	yes
MapReduce Offers an API for user-defined Map/Reduce methods		no	no	yes via Faunus, a graph analytics engine
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration		Immediate Consistency READ-COMMITTED or SERIALIZED	Eventual Consistency Immediate Consistency
Foreign keys Referential integrity	no	yes	no manual creation possible, using inversions based on multi-value capability	yes Relationships in graphs
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	ACID	ACID Optimistic locking for transactions; no isolation for bulk loads	ACID
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes		no
User concepts Access control	LDAP bind authentication	Pluggable authentication mechanisms e.g. LDAP, HTTP	no	User authentification and security via Rexster Graph Server
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More resources
	Atos Standard Common Repository	Drizzle	InfinityDB	JanusGraph successor of Titan
DB-Engines blog posts		MySQL won the April ranking; did its forks follow? 1 April 2015, Paul Andlinger Has MySQL finally lost its mojo? 1 July 2013, Matthias Gelbmann show all
Recent citations in the news				Simple Deployment of a Graph Database: JanusGraph 12 October 2020, Towards Data Science Database Deep Dives: JanusGraph 8 August 2019, ibm.com JanusGraph Picks Up Where TitanDB Left Off 13 January 2017, Datanami Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph 3 October 2019, The New Stack Compose for JanusGraph arrives on Bluemix 15 September 2017, ibm.com provided by Google News

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