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DBMS > Apache Phoenix vs. Databricks vs. QuestDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Databricks vs. QuestDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A 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 DBMSDocument 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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.databricks.comquestdb.iospark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.databricks.comquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationDatabricksQuestDB Technology IncApache Software Foundation
Initial release2014201320142014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava (Zero-GC), C++, RustScala
Server operating systemsLinux
Unix
Windows
hostedLinux
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 dateyesyesyes
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 SQLyeswith Databricks SQLSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
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
Python
R
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregatesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyes infothrough memory mapped filesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyno
More information provided by the system vendor
Apache PhoenixDatabricksQuestDBSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Relational 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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