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DBMS > Apache Phoenix vs. OpenEdge vs. Prometheus vs. QuestDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. OpenEdge vs. Prometheus vs. QuestDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonOpenEdge  Xexclude from comparisonPrometheus  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseApplication development environment with integrated database management systemOpen-source Time Series DBMS and monitoring systemA 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 DBMSRelational DBMSTime Series DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score3.45
Rank#85  Overall
#46  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.progress.com/­openedgeprometheus.ioquestdb.iospark.apache.org/­sql
Technical documentationphoenix.apache.orgdocumentation.progress.com/­output/­ua/­OpenEdge_latestprometheus.io/­docsquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationProgress Software CorporationQuestDB Technology IncApache Software Foundation
Initial release20141984201520142014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019OpenEdge 12.2, March 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJava (Zero-GC), C++, RustScala
Server operating systemsLinux
Unix
Windows
AIX
HP-UX
Linux
Solaris
Windows
Linux
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyesyes
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.noyesno infoImport of XML data possiblenono
Secondary indexesyesyesnonono
SQL infoSupport of SQLyesyes infoclose to SQL 92noSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP/JSON APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Progress proprietary ABL (Advanced Business Language).Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyesnonono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infosince Version 11.4Shardinghorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyes infoby FederationSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infothrough memory mapped filesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyUsers and groupsnono
More information provided by the system vendor
Apache PhoenixOpenEdgePrometheusQuestDBSpark 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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More resources
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