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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. IBM Db2 warehouse vs. InterSystems IRIS vs. TinkerGraph

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. IBM Db2 warehouse vs. InterSystems IRIS vs. TinkerGraph

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically 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 scalabilityA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelRelational DBMSDocument storeRelational DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
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
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitephoenix.apache.orgcloud.google.com/­datastorewww.ibm.com/­products/­db2/­warehousewww.intersystems.com/­products/­intersystems-iristinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.cls
DeveloperApache Software FoundationGoogleIBMInterSystems
Initial release20142008201420182009
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192023.3, June 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsLinux
Unix
Windows
hostedhostedAIX
Linux
macOS
Ubuntu
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesdepending on used data modelschema-free
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.nonono infoImport/export of XML data possibleyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesSQL-like query language (GQL)yesyesno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
OLE DB
JDBC
ODBC
RESTful HTTP API
TinkerPop 3
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.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
Groovy
Java
Server-side scripts infoStored proceduresuser defined functionsusing Google App EnginePL/SQL, SQL PLyesno
TriggersnoCallbacks using the Google Apps Engineyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual 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 ConsistencyImmediate Consistencynone
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyesno
More information provided by the system vendor
Apache PhoenixGoogle Cloud DatastoreIBM Db2 warehouse infoformerly named IBM dashDBInterSystems IRISTinkerGraph
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
Apache PhoenixGoogle Cloud DatastoreIBM Db2 warehouse infoformerly named IBM dashDBInterSystems IRISTinkerGraph
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