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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. Realm vs. WakandaDB

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. Realm vs. WakandaDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRealm  Xexclude from comparisonWakandaDB  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 PlatformA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSDocument storeDocument storeObject oriented 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
Score7.60
Rank#52  Overall
#9  Document stores
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitephoenix.apache.orgcloud.google.com/­datastorerealm.iowakanda.github.io
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsrealm.io/­docswakanda.github.io/­doc
DeveloperApache Software FoundationGoogleRealm, acquired by MongoDB in May 2019Wakanda SAS
Initial release2014200820142012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen SourceOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, JavaScript
Server operating systemsLinux
Unix
Windows
hostedAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nononono
Secondary indexesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)nono
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
JavaScript
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineno inforuns within the applications so server-side scripts are unnecessaryyes
TriggersnoCallbacks using the Google Apps Engineyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosnonenone
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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnoyes infoIn-Memory realmno
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)yesyes

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Apache PhoenixGoogle Cloud DatastoreRealmWakandaDB
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