DBMS > Atos Standard Common Repository vs. EsgynDB vs. FeatureBase vs. TerarkDB

System Properties Comparison Atos Standard Common Repository vs. EsgynDB vs. FeatureBase vs. TerarkDB

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	EsgynDB  Xexclude from comparison	FeatureBase  Xexclude from comparison	TerarkDB  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-class SQL-on-Hadoop solution, powered by Apache Trafodion	Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.	A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database model	Document store Key-value store	Relational DBMS	Relational DBMS	Key-value store
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.25 Rank #312   Overall #138   Relational DBMS	Score 0.31 Rank #292   Overall #135   Relational DBMS	Score 0.08 Rank #367   Overall #56   Key-value stores
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.esgyn.cn	www.featurebase.com	github.com/­bytedance/­terarkdb
Technical documentation			docs.featurebase.com	bytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
Developer	Atos Convergence Creators	Esgyn	Molecula and Pilosa Open Source Contributors	ByteDance, originally Terark
Initial release	2016	2015	2017	2016
Current release	1703		2022, May 2022
License Commercial or Open Source	commercial	commercial	commercial	commercial restricted open source version 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	C++, Java	Go	C++
Server operating systems	Linux	Linux	Linux macOS
Data scheme	Schema and schema-less with LDAP views	yes	yes	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	no	no
Secondary indexes	yes	yes	no	no
SQL Support of SQL	no	yes	SQL queries	no
APIs and other access methods	LDAP	ADO.NET JDBC ODBC	gRPC JDBC Kafka Connector ODBC	C++ API Java API
Supported programming languages	All languages with LDAP bindings	All languages supporting JDBC/ODBC/ADO.Net	Java Python	C++ Java
Server-side scripts Stored procedures	no	Java Stored Procedures		no
Triggers	yes	no	no	no
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding	Sharding	none
Replication methods Methods for redundantly storing data on multiple nodes	yes	Multi-source replication between multi datacenters	yes	none
MapReduce Offers an API for user-defined Map/Reduce methods		yes		no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency
Foreign keys Referential integrity	no	yes	yes	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	ACID	yes	no
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes, using Linux fsync	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	no	yes	yes
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	EsgynDB	FeatureBase	TerarkDB
Recent citations in the news			The 10 Hottest Big Data Startups Of 2021 18 November 2021, CRN Get Your Infrastructure Ready for Real-Time Analytics 9 March 2022, Built In Pilosa: A Scalable High Performance Bitmap Database Index 17 June 2019, hackernoon.com 32 Data and Analytics Startups That Will Go Big, According to VCs 28 September 2021, Business Insider The 10 Coolest Big Data Tools Of 2021 7 December 2021, CRN provided by Google News	A Chinese company is making the cloud 200x faster · TechNode 3 July 2017, TechNode provided by Google News

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