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DBMS > Apache Phoenix vs. EsgynDB vs. Faircom EDGE vs. ReductStore

System Properties Comparison Apache Phoenix vs. EsgynDB vs. Faircom EDGE vs. ReductStore

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonEsgynDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonReductStore  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score0.02
Rank#370  Overall
#55  Key-value stores
#157  Relational DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Websitephoenix.apache.orgwww.esgyn.cnwww.faircom.com/­products/­faircom-edgegithub.com/­reductstore
www.reduct.store
Technical documentationphoenix.apache.orgdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.reduct.store/­docs
DeveloperApache Software FoundationEsgynFairCom CorporationReductStore LLC
Initial release2014201519792023
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V3, October 20201.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoRestricted, free version availableOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaANSI C, C++C++, Rust
Server operating systemsLinux
Unix
Windows
LinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Docker
Linux
macOS
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Types
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 indexesyesyesyes
SQL infoSupport of SQLyesyesyes infoANSI SQL queries
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsJava Stored Proceduresyes info.Net, JavaScript, C/C++
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingFile partitioning infoCustomizable business rules for partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersyes infoSynchronous and asynchronous realtime replication based on transaction logs
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesyes infowhen using SQL
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQL
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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More resources
Apache PhoenixEsgynDBFaircom EDGE infoformerly c-treeEDGEReductStore
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