DBMS > Atos Standard Common Repository vs. Splice Machine vs. Stardog vs. Tkrzw

System Properties Comparison Atos Standard Common Repository vs. Splice Machine vs. Stardog vs. Tkrzw

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Splice Machine  Xexclude from comparison	Stardog  Xexclude from comparison	Tkrzw Successor of Tokyo Cabinet and Kyoto Cabinet  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	Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark	Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization	A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database model	Document store Key-value store	Relational DBMS	Graph DBMS RDF store	Key-value store
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.54 Rank #252   Overall #115   Relational DBMS	Score 2.07 Rank #122   Overall #11   Graph DBMS #6   RDF stores	Score 0.07 Rank #372   Overall #57   Key-value stores
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	splicemachine.com	www.stardog.com	dbmx.net/­tkrzw
Technical documentation		splicemachine.com/­how-it-works	docs.stardog.com
Developer	Atos Convergence Creators	Splice Machine	Stardog-Union	Mikio Hirabayashi
Initial release	2016	2014	2010	2020
Current release	1703	3.1, March 2021	7.3.0, May 2020	0.9.3, August 2020
License Commercial or Open Source	commercial	Open Source AGPL 3.0, commercial license available	commercial 60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students	Open Source Apache Version 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	Java	Java	C++
Server operating systems	Linux	Linux OS X Solaris Windows	Linux macOS Windows	Linux macOS
Data scheme	Schema and schema-less with LDAP views	yes	schema-free and OWL/RDFS-schema support	schema-free
Typing predefined data types such as float or date	optional	yes	yes	no
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 Import/export of XML data possible	no
Secondary indexes	yes	yes	yes supports real-time indexing in full-text and geospatial
SQL Support of SQL	no	yes	Yes, compatible with all major SQL variants through dedicated BI/SQL Server	no
APIs and other access methods	LDAP	JDBC Native Spark Datasource ODBC	GraphQL query language HTTP API Jena RDF API OWL RDF4J API Sesame REST HTTP Protocol SNARL SPARQL Spring Data Stardog Studio TinkerPop 3
Supported programming languages	All languages with LDAP bindings	C# C++ Java JavaScript (Node.js) Python R Scala	.Net Clojure Groovy Java JavaScript Python Ruby	C++ Java Python Ruby
Server-side scripts Stored procedures	no	yes Java	user defined functions and aggregates, HTTP Server extensions in Java	no
Triggers	yes	yes	yes via event handlers	no
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Shared Nothhing Auto-Sharding, Columnar Partitioning	none	none
Replication methods Methods for redundantly storing data on multiple nodes	yes	Multi-source replication Source-replica replication	Multi-source replication in HA-Cluster	none
MapReduce Offers an API for user-defined Map/Reduce methods		Yes, via Full Spark Integration	no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Immediate Consistency in HA-Cluster	Immediate Consistency
Foreign keys Referential integrity	no	yes	yes relationships in graphs	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	ACID	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
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	yes	yes	yes using specific database classes
User concepts Access control	LDAP bind authentication	Access rights for users, groups and roles according to SQL-standard	Access rights for users and roles	no
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More resources
	Atos Standard Common Repository	Splice Machine	Stardog	Tkrzw Successor of Tokyo Cabinet and Kyoto Cabinet
Recent citations in the news		Machine learning data pipeline outfit Splice Machine files for insolvency 26 August 2021, The Register Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ... 19 January 2021, PR Newswire Splice Machine Launches Feature Store to Simplify Feature Engineering 19 January 2021, Datanami Real-time machine learning with Splice Machine's ML Manager 17 April 2019, TechTarget How To Axe Db2 But Keep Your Code 10 March 2020, Towards Data Science provided by Google News

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