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DBMS > Apache Phoenix vs. Dolt vs. Faircom EDGE vs. Hive

System Properties Comparison Apache Phoenix vs. Dolt vs. Faircom EDGE vs. Hive

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDolt  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHive  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA MySQL compatible DBMS with Git-like versioning of data and schemaFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsdata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.02
Rank#191  Overall
#89  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Websitephoenix.apache.orggithub.com/­dolthub/­dolt
www.dolthub.com
www.faircom.com/­products/­faircom-edgehive.apache.org
Technical documentationphoenix.apache.orgdocs.dolthub.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software FoundationDoltHub IncFairCom CorporationApache Software Foundation infoinitially developed by Facebook
Initial release2014201819792012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V3, October 20203.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoANSI C, C++Java
Server operating systemsLinux
Unix
Windows
Linux
macOS
Windows
Android
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VM
Data schemeyes infolate-bound, schema-on-read capabilitiesyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes
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
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyesyes infoANSI SQL queriesSQL-like DML and DDL statements
APIs and other access methodsJDBCCLI Client
HTTP REST
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsyes infocurrently in alpha releaseyes info.Net, JavaScript, C/C++yes infouser defined functions and integration of map-reduce
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.yes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyesyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
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.yesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyOnly one user is configurable, and must be specified in the config file at startupFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles

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More resources
Apache PhoenixDoltFaircom EDGE infoformerly c-treeEDGEHive
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