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DBMS > Google Cloud Datastore vs. IBM Db2 warehouse vs. InterSystems IRIS vs. Snowflake vs. TerarkDB

System Properties Comparison Google Cloud Datastore vs. IBM Db2 warehouse vs. InterSystems IRIS vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonSnowflake  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCloud-based data warehousing serviceA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityCloud-based data warehousing service for structured and semi-structured dataA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelDocument storeRelational DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score121.33
Rank#9  Overall
#6  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecloud.google.com/­datastorewww.ibm.com/­products/­db2/­warehousewww.intersystems.com/­products/­intersystems-iriswww.snowflake.comgithub.com/­bytedance/­terarkdb
Technical documentationcloud.google.com/­datastore/­docsdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdocs.snowflake.net/­manuals/­index.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperGoogleIBMInterSystemsSnowflake Computing Inc.ByteDance, originally Terark
Initial release20082014201820142016
Current release2023.3, June 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedhostedAIX
Linux
macOS
Ubuntu
Windows
hosted
Data schemeschema-freeyesdepending on used data modelyes infosupport of semi-structured data formats (JSON, XML, Avro)schema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyesno
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.nono infoImport/export of XML data possibleyesyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)yesyesyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
OLE DB
JDBC
ODBC
RESTful HTTP API
CLI Client
JDBC
ODBC
C++ API
Java API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C++
Java
JavaScript (Node.js)
Python
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresusing Google App EnginePL/SQL, SQL PLyesuser defined functionsno
TriggersCallbacks using the Google Apps Engineyesyesno infosimilar concept for controling cloud resourcesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyesnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosyesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyesUsers with fine-grained authorization concept, user roles and pluggable authenticationno
More information provided by the system vendor
Google Cloud DatastoreIBM Db2 warehouse infoformerly named IBM dashDBInterSystems IRISSnowflakeTerarkDB
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
Google Cloud DatastoreIBM Db2 warehouse infoformerly named IBM dashDBInterSystems IRISSnowflakeTerarkDB
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