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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. Prometheus

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. Prometheus

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonPrometheus  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 Wide Column Store for rapid development using massive semi-structured datasetsOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSDocument storeWide column storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Score7.56
Rank#49  Overall
#3  Time Series DBMS
Websitephoenix.apache.orgcloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tablesprometheus.io
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsprometheus.io/­docs
DeveloperApache Software FoundationGoogleMicrosoft
Initial release2014200820122015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0
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
hostedhostedLinux
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyesNumeric data only
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 infoImport of XML data possible
Secondary indexesyesyesnono
SQL infoSupport of SQLyesSQL-like query language (GQL)nono
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIRESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsusing Google App Enginenono
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoby Federation
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 Consistencynone
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 Transactionsoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnonono
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)Access rights based on private key authentication or shared access signaturesno

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More resources
Apache PhoenixGoogle Cloud DatastoreMicrosoft Azure Table StoragePrometheus
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