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DBMS > Datomic vs. Google Cloud Datastore vs. HugeGraph vs. Interbase vs. InterSystems Caché

System Properties Comparison Datomic vs. Google Cloud Datastore vs. HugeGraph vs. Interbase vs. InterSystems Caché

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonInterbase  Xexclude from comparisonInterSystems Caché  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSLight-weight proven RDBMS infooriginally from BorlandA multi-model DBMS and application server
Primary database modelRelational DBMSDocument storeGraph DBMSRelational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score4.08
Rank#75  Overall
#41  Relational DBMS
Websitewww.datomic.comcloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
www.embarcadero.com/­products/­interbasewww.intersystems.com/­products/­cache
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docshugegraph.apache.org/­docsdocs.embarcadero.com/­products/­interbasedocs.intersystems.com
DeveloperCognitectGoogleBaiduEmbarcaderoInterSystems
Initial release20122008201819841997
Current release1.0.7075, December 20230.9InterBase 2020, December 20192018.1.4, May 2020
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2.0commercialcommercial
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 languageJava, ClojureJavaC
Server operating systemsAll OS with a Java VMhostedLinux
macOS
Unix
Android
iOS
Linux
OS X
Windows
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesdepending on used data model
Typing infopredefined data types such as float or dateyesyes, 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.nononono infoexport as XML data possibleyes
Secondary indexesyesyesyes infoalso supports composite index and range indexyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noyesyes
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
C#
C++
Java
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Engineasynchronous Gremlin script jobsyes infoInterbase procedure and trigger languageyes
TriggersBy using transaction functionsCallbacks using the Google Apps Enginenoyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBaseInterbase Change ViewsSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowvia hugegraph-sparknono
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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMultiversion concurreny controlyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
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 developmentnoyesyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsfine grained access rights according to SQL-standardAccess rights for users, groups and roles

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More resources
DatomicGoogle Cloud DatastoreHugeGraphInterbaseInterSystems Caché
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