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DBMS > Apache Phoenix vs. Atos Standard Common Repository vs. GigaSpaces vs. Google Cloud Datastore

System Properties Comparison Apache Phoenix vs. Atos Standard Common Repository vs. GigaSpaces vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelRelational DBMSDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Document store
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websitephoenix.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.gigaspaces.comcloud.google.com/­datastore
Technical documentationphoenix.apache.orgdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­datastore/­docs
DeveloperApache Software FoundationAtos Convergence CreatorsGigaspaces TechnologiesGoogle
Initial release2014201620002008
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019170315.5, September 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; Commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava, C++, .Net
Server operating systemsLinux
Unix
Windows
LinuxLinux
macOS
Solaris
Windows
hosted
Data schemeyes infolate-bound, schema-on-read capabilitiesSchema and schema-less with LDAP viewsschema-freeschema-free
Typing infopredefined data types such as float or dateyesoptionalyesyes, details here
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.noyesno infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesnoSQL-99 for query and DML statementsSQL-like query language (GQL)
APIs and other access methodsJDBCLDAPGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
All languages with LDAP bindings.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnoyesusing Google App Engine
Triggersnoyesyes, event driven architectureCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infoMap-Reduce pattern can be built with XAP task executorsyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate 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 integritynononoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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.yesyesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyLDAP bind authenticationRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache PhoenixAtos Standard Common RepositoryGigaSpacesGoogle Cloud Datastore
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