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DBMS > Apache Phoenix vs. Atos Standard Common Repository vs. BigchainDB vs. BigObject vs. Google Cloud Firestore

System Properties Comparison Apache Phoenix vs. Atos Standard Common Repository vs. BigchainDB vs. BigObject vs. Google Cloud Firestore

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonBigchainDB  Xexclude from comparisonBigObject  Xexclude from comparisonGoogle Cloud Firestore  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 networksBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAnalytic DBMS for real-time computations and queriesCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.
Primary database modelRelational DBMSDocument store
Key-value store
Document storeRelational DBMS infoa hierachical model (tree) can be imposedDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.79
Rank#212  Overall
#36  Document stores
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Websitephoenix.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.bigchaindb.combigobject.iofirebase.google.com/­products/­firestore
Technical documentationphoenix.apache.orgbigchaindb.readthedocs.io/­en/­latestdocs.bigobject.iofirebase.google.com/­docs/­firestore
DeveloperApache Software FoundationAtos Convergence CreatorsBigObject, Inc.Google
Initial release20142016201620152017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191703
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL v3commercial infofree community edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaPython
Server operating systemsLinux
Unix
Windows
LinuxLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hosted
Data schemeyes infolate-bound, schema-on-read capabilitiesSchema and schema-less with LDAP viewsschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesoptionalnoyesyes
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.noyesnonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statementsno
APIs and other access methodsJDBCLDAPCLI Client
RESTful HTTP API
fluentd
ODBC
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
All languages with LDAP bindingsGo
Haskell
Java
JavaScript
Python
Ruby
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Server-side scripts infoStored proceduresuser defined functionsnoLuayes, Firebase Rules & Cloud Functions
Triggersnoyesnoyes, with Cloud Functions
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesselectable replication factornoneMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoUsing Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate Consistency
Foreign keys infoReferential integritynononoyes infoautomatically between fact table and dimension tablesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoRead/write lock on objects (tables, trees)yes
Durability infoSupport for making data persistentyesyesyes,with MongoDB ord RethinkDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyLDAP bind authenticationyesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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More resources
Apache PhoenixAtos Standard Common RepositoryBigchainDBBigObjectGoogle Cloud Firestore
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