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DBMS > Datomic vs. DuckDB vs. Google Cloud Datastore vs. Ingres

System Properties Comparison Datomic vs. DuckDB vs. Google Cloud Datastore vs. Ingres

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDuckDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIngres  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn embeddable, in-process, column-oriented SQL OLAP RDBMSAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWell established RDBMS
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Websitewww.datomic.comduckdb.orgcloud.google.com/­datastorewww.actian.com/­databases/­ingres
Technical documentationdocs.datomic.comduckdb.org/­docscloud.google.com/­datastore/­docsdocs.actian.com/­ingres
DeveloperCognitectGoogleActian Corporation
Initial release2012201820081974 infooriginally developed at University Berkely in early 1970s
Current release1.0.7075, December 20231.0.0, June 202411.2, May 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoMIT Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++C
Server operating systemsAll OS with a Java VMserver-lesshostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)yes
APIs and other access methodsRESTful HTTP APIArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Supported programming languagesClojure
Java
C
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
Server-side scripts infoStored proceduresyes infoTransaction Functionsnousing Google App Engineyes
TriggersBy using transaction functionsnoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneously
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneMulti-source replication using PaxosIngres Replicator
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes infoMVCC
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesnono
User concepts infoAccess controlnonoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
DatomicDuckDBGoogle Cloud DatastoreIngres
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