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DBMS > Google BigQuery vs. Google Cloud Spanner vs. Kinetica

System Properties Comparison Google BigQuery vs. Google Cloud Spanner vs. Kinetica

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesA 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.Fully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score62.88
Rank#19  Overall
#13  Relational DBMS
Score2.56
Rank#97  Overall
#50  Relational DBMS
Score0.50
Rank#247  Overall
#116  Relational DBMS
Websitecloud.google.com/­bigquerycloud.google.com/­spannerwww.kinetica.com
Technical documentationcloud.google.com/­bigquery/­docscloud.google.com/­spanner/­docsdocs.kinetica.com
DeveloperGoogleGoogleKinetica
Initial release201020172012
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++
Server operating systemshostedhostedLinux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesnoyesyes
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP/JSON APIgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnouser defined functions
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
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 datano infoSince BigQuery is designed for querying dataACID infoStrict serializable isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table level

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More resources
Google BigQueryGoogle Cloud SpannerKinetica
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