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DBMS > Google Cloud Spanner vs. ObjectBox vs. Sphinx vs. Teradata

System Properties Comparison Google Cloud Spanner vs. ObjectBox vs. Sphinx vs. Teradata

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonObjectBox  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA 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.Extremely fast embedded database for small devices, IoT and MobileOpen source search engine for searching in data from different sources, e.g. relational databasesA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSObject oriented DBMSSearch engineRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitecloud.google.com/­spannerobjectbox.iosphinxsearch.comwww.teradata.com
Technical documentationcloud.google.com/­spanner/­docsdocs.objectbox.iosphinxsearch.com/­docsdocs.teradata.com
DeveloperGoogleObjectBox LimitedSphinx Technologies Inc.Teradata
Initial release2017201720011984
Current release3.5.1, February 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0Open Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++
Server operating systemshostedAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
hosted
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonoyes
Secondary indexesyesyesyes infofull-text index on all search fieldsyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011noSQL-like query language (SphinxQL)yes infoSQL 2016 + extensions
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Proprietary native APIProprietary protocol.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnononoyes infoUDFs, stored procedures, table functions in parallel
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.online/offline synchronization between client and servernoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesnofine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud SpannerObjectBoxSphinxTeradata
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More resources
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11 October 2023, TechCrunch

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12 October 2023, TechRadar

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