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DBMS > DuckDB vs. Google Cloud Datastore vs. Percona Server for MongoDB vs. Sequoiadb vs. Spark SQL

System Properties Comparison DuckDB vs. Google Cloud Datastore vs. Percona Server for MongoDB vs. Sequoiadb vs. Spark SQL

Editorial information provided by DB-Engines
NameDuckDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPercona Server for MongoDB  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 PlatformA drop-in replacement for MongoDB Community Edition with enterprise-grade features.NewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeDocument storeDocument store
Relational DBMS
Relational 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
Score0.52
Rank#254  Overall
#39  Document stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteduckdb.orgcloud.google.com/­datastorewww.percona.com/­mongodb/­software/­percona-server-for-mongodbwww.sequoiadb.comspark.apache.org/­sql
Technical documentationduckdb.org/­docscloud.google.com/­datastore/­docsdocs.percona.com/­percona-distribution-for-mongodbwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGooglePerconaSequoiadb Ltd.Apache Software Foundation
Initial release20182008201520132014
Current release0.10, February 20243.4.10-2.10, November 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoGPL Version 2Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
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-lesshostedLinuxLinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeschema-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.nonononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesSQL-like query language (GQL)noSQL-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
proprietary protocol using JSONproprietary 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
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnousing Google App EngineJavaScriptJavaScriptno
TriggersnoCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
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.Eventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoDocument 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.yesnoyes infovia In-Memory Enginenono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolessimple password-based access controlno

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More resources
DuckDBGoogle Cloud DatastorePercona Server for MongoDBSequoiadbSpark SQL
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