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DBMS > Google BigQuery vs. Google Cloud Datastore

System Properties Comparison Google BigQuery vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score36.00
Rank#24  Overall
#15  Relational DBMS
Score5.27
Rank#71  Overall
#12  Document stores
Websitecloud.google.com/­bigquerycloud.google.com/­datastore
Technical documentationcloud.google.com/­bigquery/­docscloud.google.com/­datastore/­docs
DeveloperGoogleGoogle
Initial release20102008
License infoCommercial or Open Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Server operating systemshostedhosted
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details here
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 indexesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)
APIs and other access methodsRESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptusing Google App Engine
TriggersnoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess privileges (owner, writer, reader) for whole datasets, not for individual tables infoGoogle Cloud Identity & Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Google BigQueryGoogle Cloud Datastore
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