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DBMS > Hypertable vs. Oracle vs. Spark SQL

System Properties Comparison Hypertable vs. Oracle vs. Spark SQL

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonOracle  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopWidely used RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Oracle Spatial and Graph
RDF store infowith Oracle Spatial and Graph
Spatial DBMS infowith Oracle Spatial and Graph
Vector DBMS infosince Oracle 23
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1221.06
Rank#1  Overall
#1  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websitewww.oracle.com/­databasespark.apache.org/­sql
Technical documentationdocs.oracle.com/­en/­databasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHypertable Inc.OracleApache Software Foundation
Initial release200919802014
Current release0.9.8.11, March 201623c, September 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availablecommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++Scala
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS
Linux
OS X
Windows
Data schemeschema-freeyes infoSchemaless in JSON and XML columnsyes
Typing infopredefined data types such as float or datenoyesyes
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.yesno
Secondary indexesrestricted infoonly exact value or prefix value scansyesno
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsC++ API
Thrift
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
JDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoPL/SQL infoalso stored procedures in Java possibleno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno infocan be realized in PL/SQL
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoisolation level can be parameterizedno
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.yes infoVersion 12c introduced the new option 'Oracle Database In-Memory'no
User concepts infoAccess controlnofine grained access rights according to SQL-standardno

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HypertableOracleSpark SQL
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