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DBMS > Apache Phoenix vs. BigchainDB vs. Citus vs. Google Cloud Datastore vs. Heroic

System Properties Comparison Apache Phoenix vs. BigchainDB vs. Citus vs. Google Cloud Datastore vs. Heroic

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBigchainDB  Xexclude from comparisonCitus  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHeroic  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelRelational DBMSDocument storeRelational DBMSDocument storeTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Websitephoenix.apache.orgwww.bigchaindb.comwww.citusdata.comcloud.google.com/­datastoregithub.com/­spotify/­heroic
Technical documentationphoenix.apache.orgbigchaindb.readthedocs.io/­en/­latestdocs.citusdata.comcloud.google.com/­datastore/­docsspotify.github.io/­heroic
DeveloperApache Software FoundationGoogleSpotify
Initial release20142016201020082014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20198.1, December 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL v3Open Source infoAGPL, commercial license also availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaPythonCJava
Server operating systemsLinux
Unix
Windows
LinuxLinuxhosted
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesyes, 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.nonoyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesyesyes infovia Elasticsearch
SQL infoSupport of SQLyesnoyes infostandard, with numerous extensionsSQL-like query language (GQL)no
APIs and other access methodsJDBCCLI Client
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.using Google App Engineno
TriggersnoyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate 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.Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
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-tenancyyesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache PhoenixBigchainDBCitusGoogle Cloud DatastoreHeroic
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