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DBMS > Google Cloud Spanner vs. Hive vs. InfinityDB vs. MonetDB

System Properties Comparison Google Cloud Spanner vs. Hive vs. InfinityDB vs. MonetDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonHive  Xexclude from comparisonInfinityDB  Xexclude from comparisonMonetDB  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.data warehouse software for querying and managing large distributed datasets, built on HadoopA Java embedded Key-Value Store which extends the Java Map interfaceA relational database management system that stores data in columns
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#105  Overall
#53  Relational DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score0.07
Rank#359  Overall
#54  Key-value stores
Score1.72
Rank#148  Overall
#68  Relational DBMS
Websitecloud.google.com/­spannerhive.apache.orgboilerbay.comwww.monetdb.org
Technical documentationcloud.google.com/­spanner/­docscwiki.apache.org/­confluence/­display/­Hive/­Homeboilerbay.com/­infinitydb/­manualwww.monetdb.org/­Documentation
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookBoiler Bay Inc.MonetDB BV
Initial release2017201220022004
Current release3.1.3, April 20224.0Dec2023 (11.49), December 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoMozilla Public License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemshostedAll OS with a Java VMAll OS with a Java VMFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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.nono
Secondary indexesyesyesno infomanual creation possible, using inversions based on multi-value capabilityyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statementsnoyes infoSQL 2003 with some 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
JDBC
ODBC
Thrift
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
JavaC
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenoyes, in SQL, C, R
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding via remote tables
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.selectable replication factornonenone infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono infomanual creation possible, using inversions based on multi-value capabilityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationnoACID infoOptimistic locking for transactions; no isolation for bulk loadsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesnofine grained access rights according to SQL-standard

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More resources
Google Cloud SpannerHiveInfinityDBMonetDB
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