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DBMS > Hypertable vs. Spark SQL vs. SQream DB vs. Tkrzw

System Properties Comparison Hypertable vs. Spark SQL vs. SQream DB vs. Tkrzw

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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 HadoopSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelWide column storeRelational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitespark.apache.org/­sqlsqream.comdbmx.net/­tkrzw
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperHypertable Inc.Apache Software FoundationSQream TechnologiesMikio Hirabayashi
Initial release2009201420172020
Current release0.9.8.11, March 20163.5.0 ( 2.13), September 20232022.1.6, December 20220.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++, CUDA, Haskell, Java, ScalaC++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Windows
LinuxLinux
macOS
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyes, ANSI Standard SQL Typesno
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
Secondary indexesrestricted infoonly exact value or prefix value scansnono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesno
APIs and other access methodsC++ API
Thrift
JDBC
ODBC
.Net
JDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnonouser defined functions in Pythonno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corehorizontal and vertical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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.noyes infousing specific database classes
User concepts infoAccess controlnonono

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HypertableSpark SQLSQream DBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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