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DBMS > Google BigQuery vs. PlanetScale vs. SingleStore

System Properties Comparison Google BigQuery vs. PlanetScale vs. SingleStore

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonPlanetScale  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesScalable, distributed, serverless MySQL database platform built on top of VitessMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.73
Rank#19  Overall
#13  Relational DBMS
Score1.00
Rank#180  Overall
#80  Relational DBMS
Score3.93
Rank#69  Overall
#37  Relational DBMS
Websitecloud.google.com/­bigqueryplanetscale.comwww.singlestore.com
Technical documentationcloud.google.com/­bigquery/­docsplanetscale.com/­docsdocs.singlestore.com
DeveloperGooglePlanetScaleSingleStore Inc.
Initial release201020202013
Current release8.5, January 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++, Go
Server operating systemshostedDocker
Linux
macOS
Linux info64 bit version required
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.nono
Secondary indexesnoyesyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsyes infobut no triggers and foreign keys
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
JDBC
MySQL protocol
ODBC
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes infoproprietary syntaxyes
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integritynoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Users with fine-grained authorization concept infono user groups or rolesFine grained access control via users, groups and roles

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More resources
Google BigQueryPlanetScaleSingleStore infoformer name was MemSQL
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