DBMS > Atos Standard Common Repository vs. KairosDB vs. Sadas Engine vs. Splice Machine

System Properties Comparison Atos Standard Common Repository vs. KairosDB vs. Sadas Engine vs. Splice Machine

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	KairosDB  Xexclude from comparison	Sadas Engine  Xexclude from comparison	Splice Machine  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	Distributed Time Series DBMS based on Cassandra or H2	SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments	Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database model	Document store Key-value store	Time Series DBMS	Relational DBMS	Relational DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.67 Rank #233   Overall #20   Time Series DBMS	Score 0.07 Rank #373   Overall #157   Relational DBMS	Score 0.54 Rank #252   Overall #115   Relational DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	github.com/­kairosdb/­kairosdb	www.sadasengine.com	splicemachine.com
Technical documentation		kairosdb.github.io	www.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation	splicemachine.com/­how-it-works
Developer	Atos Convergence Creators		SADAS s.r.l.	Splice Machine
Initial release	2016	2013	2006	2014
Current release	1703	1.2.2, November 2018	8.0	3.1, March 2021
License Commercial or Open Source	commercial	Open Source Apache 2.0	commercial free trial version available	Open Source AGPL 3.0, commercial license available
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	C++	Java
Server operating systems	Linux	Linux OS X Windows	AIX Linux Windows	Linux OS X Solaris Windows
Data scheme	Schema and schema-less with LDAP views	schema-free	yes	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	no	yes	yes
SQL Support of SQL	no	no	yes	yes
APIs and other access methods	LDAP	Graphite protocol HTTP REST Telnet API	JDBC ODBC Proprietary protocol	JDBC Native Spark Datasource ODBC
Supported programming languages	All languages with LDAP bindings	Java JavaScript Node.js PHP Python	.Net C C# C++ Groovy Java PHP Python	C# C++ Java JavaScript (Node.js) Python R Scala
Server-side scripts Stored procedures	no	no	no	yes Java
Triggers	yes	no	no	yes
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding based on Cassandra	horizontal partitioning	Shared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods Methods for redundantly storing data on multiple nodes	yes	selectable replication factor based on Cassandra	none	Multi-source replication Source-replica replication
MapReduce Offers an API for user-defined Map/Reduce methods		no	no	Yes, via Full Spark Integration
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra	Immediate Consistency	Immediate Consistency
Foreign keys Referential integrity	no	no	yes	yes
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	no		ACID
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes, multi-version concurrency control (MVCC)
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	yes managed by 'Learn by Usage'	yes
User concepts Access control	LDAP bind authentication	simple password-based access control	Access rights for users, groups and roles according to SQL-standard	Access rights for users, groups and roles according to SQL-standard
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More resources
	Atos Standard Common Repository	KairosDB	Sadas Engine	Splice Machine
Recent citations in the news		Real-Time Performance and Health Monitoring Using Netdata 2 September 2019, CNX Software Expo: Real Time A/B Testing and Monitoring with Spark Streaming and Kafka at Walmart Labs 24 May 2019, InfoQ.com provided by Google News		Machine learning data pipeline outfit Splice Machine files for insolvency 26 August 2021, The Register Splice Machine Launches Feature Store to Simplify Feature Engineering 19 January 2021, Datanami New Splice Machine RDBMS unites OLTP and OLAP 18 November 2015, CIO Big Data News: Splice Machine, Carpathia, Altiscale, DataGravity 11 February 2014, Data Center Knowledge How To Axe Db2 But Keep Your Code 10 March 2020, Towards Data Science provided by Google News

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