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DBMS > Atos Standard Common Repository vs. BigObject vs. Oracle Berkeley DB vs. Splice Machine

System Properties Comparison Atos Standard Common Repository vs. BigObject vs. Oracle Berkeley DB vs. Splice Machine

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBigObject  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSplice Machine  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksAnalytic DBMS for real-time computations and queriesWidely used in-process key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Key-value store
Relational DBMS infoa hierachical model (tree) can be imposedKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorybigobject.iowww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsplicemachine.com
Technical documentationdocs.bigobject.iodocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsBigObject, Inc.Oracle infooriginally developed by Sleepycat, which was acquired by OracleSplice Machine
Initial release2016201519942014
Current release170318.1.40, May 20203.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infocommercial license availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infoSQL interfaced based on SQLite is availableyes
APIs and other access methodsLDAPfluentd
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages with LDAP bindings.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoLuanoyes infoJava
Triggersyesnoyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnonenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlLDAP bind authenticationnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Atos Standard Common RepositoryBigObjectOracle Berkeley DBSplice Machine
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