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

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonQdrant  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 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.A high-performance vector database with neural network or semantic-based matchingOpen-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 DBMSVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score1.28
Rank#167  Overall
#6  Vector DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­spannergithub.com/­qdrant/­qdrant
qdrant.tech
splicemachine.com
Technical documentationcloud.google.com/­spanner/­docsqdrant.tech/­documentationsplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsGoogleQdrantSplice Machine
Initial release2016201720212014
Current release17033.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustJava
Server operating systemsLinuxhostedDocker
Linux
macOS
Windows
Linux
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesNumbers, Strings, Geo, Booleanyes
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
Secondary indexesyesyesyes infoKeywords, numberic ranges, geo, full-textyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011noyes
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
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages with LDAP bindingsGo
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoJava
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication with 3 replicas for regional instances.Collection-level replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency, tunable consistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, 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.yesnoyesyes
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Key-based authenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
Atos Standard Common RepositoryGoogle Cloud SpannerQdrantSplice Machine
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