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DBMS > Apache Spark (SQL) vs. QuestDB vs. SAP HANA

System Properties Comparison Apache Spark (SQL) vs. QuestDB vs. SAP HANA

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonQuestDB  Xexclude from comparisonSAP HANA  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingA high performance open source SQL database for time series dataIn-memory, column based data store. Available as appliance or cloud service
Primary database modelRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.40
Rank#29  Overall
#18  Relational DBMS
Score3.12
Rank#81  Overall
#6  Time Series DBMS
Score33.40
Rank#23  Overall
#16  Relational DBMS
Websitespark.apache.org/­sqlquestdb.iowww.sap.com/­products/­hana.html
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlquestdb.io/­docshelp.sap.com/­hana
DeveloperApache Software FoundationQuestDB Technology IncSAP
Initial release201420142010
Current release3.5.0 ( 2.13), September 20232.0 SPS07 (April 4, 2023), April 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono infoalso available as a cloud based service
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJava (Zero-GC), C++, Rust
Server operating systemsLinux
OS X
Windows
Linux
macOS
Windows
Appliance or cloud-service
Data schemeyesyes 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.nonono
Secondary indexesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL with time-series extensionsyes
APIs and other access methodsJDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesJava
Python
R
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnonoSQLScript, R
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corehorizontal partitioning (by timestamps)yes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication with eventual consistencyyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID for single-table writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infothrough memory mapped filesyes
User concepts infoAccess controlnoyes

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More resources
Apache Spark (SQL)QuestDBSAP HANA
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