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DBMS > Apache Phoenix vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. gStore

System Properties Comparison Apache Phoenix vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. gStore

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisongStore  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA native Graph DBMS to store and maintain very large RDF datasets.
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.14
Rank#342  Overall
#34  Graph DBMS
#16  RDF stores
Websitephoenix.apache.orgcloud.google.com/­bigtablecloud.google.com/­datastoreen.gstore.cn
Technical documentationphoenix.apache.orgcloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docsen.gstore.cn/­#/­enDocs
DeveloperApache Software FoundationGoogleGoogle
Initial release2014201520082016
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.2, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinux
Unix
Windows
hostedhostedLinux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesnoyes, details hereyes
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 indexesyesnoyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)no
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
SPARQL 1.1
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnousing Google App Engineyes
TriggersnonoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate 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.
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes
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 for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissions, Role-Based Access Control (RBAC) supported

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More resources
Apache PhoenixGoogle Cloud BigtableGoogle Cloud DatastoregStore
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