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DBMS > DuckDB vs. Google Cloud Datastore vs. Spark SQL vs. Stardog

System Properties Comparison DuckDB vs. Google Cloud Datastore vs. Spark SQL vs. Stardog

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Editorial information provided by DB-Engines
NameDuckDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionAn embeddable, in-process, column-oriented SQL OLAP RDBMSAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSDocument storeRelational DBMSGraph DBMS
RDF store
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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteduckdb.orgcloud.google.com/­datastorespark.apache.org/­sqlwww.stardog.com
Technical documentationduckdb.org/­docscloud.google.com/­datastore/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperGoogleApache Software FoundationStardog-Union
Initial release2018200820142010
Current release0.10, February 20243.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ScalaJava
Server operating systemsserver-lesshostedLinux
OS X
Windows
Linux
macOS
Windows
Data schemeyesschema-freeyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nononono infoImport/export of XML data possible
Secondary indexesyesyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
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
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Enginenouser defined functions and aggregates, HTTP Server extensions in Java
TriggersnoCallbacks using the Google Apps Enginenoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
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 Consistency in HA-Cluster
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
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.yesnonoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users and roles

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More resources
DuckDBGoogle Cloud DatastoreSpark SQLStardog
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