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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. Hyprcubd vs. InterSystems Caché

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. Hyprcubd vs. InterSystems Caché

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHyprcubd  Xexclude from comparisonInterSystems Caché  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformServerless Time Series DBMSA multi-model DBMS and application server
Primary database modelRelational DBMSDocument storeTime Series 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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websitephoenix.apache.orgcloud.google.com/­datastorehyprcubd.com (offline)www.intersystems.com/­products/­cache
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsdocs.intersystems.com
DeveloperApache Software FoundationGoogleHyprcubd, Inc.InterSystems
Initial release201420081997
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192018.1.4, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemsLinux
Unix
Windows
hostedhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyesyes, details hereyes infotime, int, uint, float, stringyes
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 indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query languageyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC (https).NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
Server-side scripts infoStored proceduresuser defined functionsusing Google App Enginenoyes
TriggersnoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infousing Google Cloud Dataflownono
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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesnoyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
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)token accessAccess rights for users, groups and roles

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More resources
Apache PhoenixGoogle Cloud DatastoreHyprcubdInterSystems Caché
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