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DBMS > Apache Phoenix vs. GeoSpock vs. HBase vs. QuestDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. GeoSpock vs. HBase vs. QuestDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGeoSpock  Xexclude from comparisonHBase  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseSpatial and temporal data processing engine for extreme data scaleWide-column store based on Apache Hadoop and on concepts of BigTableA 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 DBMSWide column storeTime Series DBMSRelational DBMS
Secondary database modelsTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orggeospock.comhbase.apache.orgquestdb.iospark.apache.org/­sql
Technical documentationphoenix.apache.orghbase.apache.org/­book.htmlquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGeoSpockApache Software Foundation infoApache top-level project, originally developed by PowersetQuestDB Technology IncApache Software Foundation
Initial release2014200820142014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.0, September 20192.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, JavascriptJavaJava (Zero-GC), C++, RustScala
Server operating systemsLinux
Unix
Windows
hostedLinux
Unix
Windows infousing Cygwin
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-free, schema definition possibleyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyesyes
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.nonononono
Secondary indexesyestemporal, categoricalnonono
SQL infoSupport of SQLyesANSI SQL for query only (using Presto)noSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBCJava API
RESTful HTTP API
Thrift
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++
Groovy
Java
PHP
Python
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnoyes infoCoprocessors in Javanono
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingShardinghorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Source-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)ACID 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.yesnoyesyes infothrough memory mapped filesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users can be defined per tableAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno
More information provided by the system vendor
Apache PhoenixGeoSpockHBaseQuestDBSpark 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
Apache PhoenixGeoSpockHBaseQuestDBSpark SQL
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