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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfluxDB  Xexclude from comparisonRealm  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 PlatformDBMS for storing time series, events and metricsA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMSDocument storeTime Series DBMSDocument store
Secondary database modelsSpatial DBMS infowith GEO package
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
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Websitephoenix.apache.orgcloud.google.com/­datastorewww.influxdata.com/­products/­influxdb-overviewrealm.io
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsdocs.influxdata.com/­influxdbrealm.io/­docs
DeveloperApache Software FoundationGoogleRealm, acquired by MongoDB in May 2019
Initial release2014200820132014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.7.6, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGo
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X infothrough Homebrew
Android
Backend: server-less
iOS
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereNumeric data and Stringsyes
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 indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query languageno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JSON over UDP
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresuser defined functionsusing Google App Enginenono inforuns within the applications so server-side scripts are unnecessary
TriggersnoCallbacks using the Google Apps Enginenoyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoin enterprise version onlynone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosselectable replication factor infoin enterprise version onlynone
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 Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
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 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 infoDepending on used storage engineyes infoIn-Memory realm
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)simple rights management via user accountsyes
More information provided by the system vendor
Apache PhoenixGoogle Cloud DatastoreInfluxDBRealm
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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