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DBMS > Hypertable vs. Spark SQL vs. Trafodion vs. VictoriaMetrics

System Properties Comparison Hypertable vs. Spark SQL vs. Trafodion vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded 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 processingTransactional SQL-on-Hadoop DBMSA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelWide column storeRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitespark.apache.org/­sqltrafodion.apache.orgvictoriametrics.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperHypertable Inc.Apache Software FoundationApache Software Foundation, originally developed by HPVictoriaMetrics
Initial release2009201420142018
Current release0.9.8.11, March 20163.5.0 ( 2.13), September 20232.3.0, February 2019v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ScalaC++, JavaGo
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Windows
LinuxFreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeyesyes
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.nonono
Secondary indexesrestricted infoonly exact value or prefix value scansnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesno
APIs and other access methodsC++ API
Thrift
JDBC
ODBC
ADO.NET
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnonoJava Stored Proceduresno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelnoneyes, via HBaseSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
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.nonono
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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More resources
HypertableSpark SQLTrafodionVictoriaMetrics
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