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DBMS > Databend vs. Datomic vs. Google Cloud Datastore vs. InterSystems Caché

System Properties Comparison Databend vs. Datomic vs. Google Cloud Datastore vs. InterSystems Caché

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  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.
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityDatomic 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 multi-model DBMS and application server
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.datomic.comcloud.google.com/­datastorewww.intersystems.com/­products/­cache
Technical documentationdocs.databend.comdocs.datomic.comcloud.google.com/­datastore/­docsdocs.intersystems.com
DeveloperDatabend LabsCognitectGoogleInterSystems
Initial release2021201220081997
Current release1.0.59, April 20231.0.6735, June 20232018.1.4, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freecommercialcommercial
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 languageRustJava, Clojure
Server operating systemshosted
Linux
macOS
All OS with a Java VMhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freedepending on used data model
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.nononoyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)yes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Clojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsusing Google App Engineyes
TriggersnoBy using transaction functionsCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersMulti-source replication using PaxosSource-replica replication
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 datayesACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 developmentnoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles

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DatabendDatomicGoogle Cloud DatastoreInterSystems Caché
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