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

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

Editorial information provided by DB-Engines
NameDuckDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, in-process, column-oriented SQL OLAP RDBMSAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase as a Service offering with high compatibility to Microsoft SQL ServerNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeRelational DBMSDocument store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.57
Rank#74  Overall
#40  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteduckdb.orgcloud.google.com/­datastoreazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.sequoiadb.comspark.apache.org/­sql
Technical documentationduckdb.org/­docscloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleMicrosoftSequoiadb Ltd.Apache Software Foundation
Initial release20182008201020132014
Current release0.10, February 2024V123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialcommercialOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++Scala
Server operating systemsserver-lesshostedhostedLinuxLinux
OS X
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infooid, date, timestamp, binary, regexyes
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.nonoyesnono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesSQL-like query language (GQL)yesSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnousing Google App EngineTransact SQLJavaScriptno
TriggersnoCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using Paxosyes, with always 3 replicas availableSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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.Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardsimple password-based access controlno

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More resources
DuckDBGoogle Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzureSequoiadbSpark SQL
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