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

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

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonPrometheus  Xexclude from comparisonQuestDB  Xexclude from comparisonRisingWave  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseOpen-source Time Series DBMS and monitoring systemA high performance open source SQL database for time series dataA distributed RDBMS for stream processing, wire-compatible with PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSRelational 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
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.64
Rank#238  Overall
#110  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgprometheus.ioquestdb.iowww.risingwave.com/­databasespark.apache.org/­sql
Technical documentationphoenix.apache.orgprometheus.io/­docsquestdb.io/­docsdocs.risingwave.com/­docs/­current/­introspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationQuestDB Technology IncRisingWave LabsApache Software Foundation
Initial release20142015201420222014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.2, September 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoJava (Zero-GC), C++, RustRustScala
Server operating systemsLinux
Unix
Windows
Linux
Windows
Linux
macOS
Windows
Docker
Linux
macOS
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyes infoschema-free via InfluxDB Line Protocolyesyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyesStandard SQL-types and JSONyes
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.nono infoImport of XML data possiblenonono
Secondary indexesyesnonoyesno
SQL infoSupport of SQLyesnoSQL with time-series extensionsyesSQL-like DML and DDL statements
APIs and other access methodsJDBCRESTful HTTP/JSON APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnonoUDFs in Python or Javano
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes 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 ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID for single-table writesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyes infothrough memory mapped filesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoUsers and Rolesno
More information provided by the system vendor
Apache PhoenixPrometheusQuestDBRisingWaveSpark 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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache PhoenixPrometheusQuestDBRisingWaveSpark SQL
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