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DBMS > Apache Phoenix vs. Faircom EDGE vs. QuestDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Faircom EDGE vs. QuestDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.faircom.com/­products/­faircom-edgequestdb.iospark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationFairCom CorporationQuestDB Technology IncApache Software Foundation
Initial release2014197920142014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V3, October 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++Java (Zero-GC), C++, RustScala
Server operating systemsLinux
Unix
Windows
Android
Linux infoARM, x86
Raspbian
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes
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.noyesnono
Secondary indexesyesyesnono
SQL infoSupport of SQLyesyes infoANSI SQL queriesSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBCADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++nono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioninghorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoSynchronous and asynchronous realtime replication based on transaction logsSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
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.yesyesyes infothrough memory mapped filesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.no
More information provided by the system vendor
Apache PhoenixFaircom EDGE infoformerly c-treeEDGEQuestDBSpark SQL
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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