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DBMS > Atos Standard Common Repository vs. Google Cloud Spanner vs. LevelDB vs. Splice Machine vs. TimescaleDB

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Spanner vs. LevelDB vs. Splice Machine vs. TimescaleDB

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonLevelDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimescaleDB  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 networksA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Key-value store
Relational DBMSKey-value storeRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­spannergithub.com/­google/­leveldbsplicemachine.comwww.timescale.com
Technical documentationcloud.google.com/­spanner/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsplicemachine.com/­how-it-worksdocs.timescale.com
DeveloperAtos Convergence CreatorsGoogleGoogleSplice MachineTimescale
Initial release20162017201120142017
Current release17031.23, February 20213.1, March 20212.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaC
Server operating systemsLinuxhostedIllumos
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyesyes
Typing infopredefined data types such as float or dateoptionalyesnoyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesnonoyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011noyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsLDAPgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages with LDAP bindingsGo
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnononoyes infoJavauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication with 3 replicas for regional instances.noneMulti-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID infoStrict serializable isolationnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryGoogle Cloud SpannerLevelDBSplice MachineTimescaleDB
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