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DBMS > Atos Standard Common Repository vs. Google Cloud Datastore vs. Prometheus vs. Sphinx vs. Splice Machine

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Datastore vs. Prometheus vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPrometheus  Xexclude from comparisonSphinx  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 networksAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen-source Time Series DBMS and monitoring systemOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-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
Document storeTime Series DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­datastoreprometheus.iosphinxsearch.comsplicemachine.com
Technical documentationcloud.google.com/­datastore/­docsprometheus.io/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsGoogleSphinx Technologies Inc.Splice Machine
Initial release20162008201520012014
Current release17033.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++Java
Server operating systemsLinuxhostedLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeyesyesyes
Typing infopredefined data types such as float or dateoptionalyes, details hereNumeric data onlynoyes
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.yesnono infoImport of XML data possible
Secondary indexesyesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like query language (SphinxQL)yes
APIs and other access methodsLDAPgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP/JSON APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnousing Google App Enginenonoyes infoJava
TriggersyesCallbacks using the Google Apps Enginenonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes infoby FederationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.noneImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Atos Standard Common RepositoryGoogle Cloud DatastorePrometheusSphinxSplice Machine
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