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DBMS > Google Cloud Datastore vs. Microsoft Azure SQL Database vs. QuestDB vs. Spark SQL

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure SQL Database vs. QuestDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase as a Service offering with high compatibility to Microsoft SQL ServerA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­en-us/­products/­azure-sql/­databasequestdb.iospark.apache.org/­sql
Technical documentationcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleMicrosoftQuestDB Technology IncApache Software Foundation
Initial release2008201020142014
Current releaseV123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java (Zero-GC), C++, RustScala
Server operating systemshostedhostedLinux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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.noyesnono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like query language (GQL)yesSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresusing Google App EngineTransact SQLnono
TriggersCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes, with always 3 replicas availableSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID for single-table writesno
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.noyes infothrough memory mapped filesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno
More information provided by the system vendor
Google Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzureQuestDBSpark SQL
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Google Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzureQuestDBSpark SQL
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