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DBMS > Databend vs. Google Cloud Datastore vs. InterSystems IRIS vs. LokiJS vs. mSQL

System Properties Comparison Databend vs. Google Cloud Datastore vs. InterSystems IRIS vs. LokiJS vs. mSQL

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonLokiJS  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityIn-memory JavaScript DBMSmSQL (Mini SQL) is a simple and lightweight RDBMS
Primary database modelRelational DBMSDocument storeDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score3.54
Rank#84  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score0.49
Rank#260  Overall
#42  Document stores
Score1.27
Rank#169  Overall
#76  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­datastorewww.intersystems.com/­products/­intersystems-irisgithub.com/­techfort/­LokiJShughestech.com.au/­products/­msql
Technical documentationdocs.databend.comcloud.google.com/­datastore/­docsdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clstechfort.github.io/­LokiJS
DeveloperDatabend LabsGoogleInterSystemsHughes Technologies
Initial release20212008201820141994
Current release1.0.59, April 20232023.3, June 20234.4, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Sourcecommercial infofree licenses can be provided
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 languageRustJavaScriptC
Server operating systemshosted
Linux
macOS
hostedAIX
Linux
macOS
Ubuntu
Windows
server-less, requires a JavaScript environment (browser, Node.js)AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesschema-freedepending on used data modelschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyesnoyes
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.nonoyesnono
Secondary indexesnoyesyesyes infovia viewsyes
SQL infoSupport of SQLyesSQL-like query language (GQL)yesnoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggers
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
JavaScript APIJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
JavaScript (Node.js)
Python
JavaScriptC
C++
Delphi
Java
Perl
PHP
Tcl
Server-side scripts infoStored proceduresnousing Google App EngineyesView functions in JavaScriptno
TriggersnoCallbacks using the Google Apps Engineyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyesno
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 Consistencynonenone
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno infoatomic operations within a single collection possibleno
Concurrency infoSupport for concurrent manipulation of datayesyesyesno
Durability infoSupport for making data persistentyesyesyesyes infoSerialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesnono
More information provided by the system vendor
DatabendGoogle Cloud DatastoreInterSystems IRISLokiJSmSQL infoMini SQL
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
DatabendGoogle Cloud DatastoreInterSystems IRISLokiJSmSQL infoMini SQL
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