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DBMS > Hypertable vs. OrigoDB vs. Riak KV vs. Spark SQL

System Properties Comparison Hypertable vs. OrigoDB vs. Riak KV vs. Spark SQL

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonOrigoDB  Xexclude from comparisonRiak KV  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 HadoopA fully ACID in-memory object graph databaseDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeDocument store
Object oriented DBMS
Key-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteorigodb.comspark.apache.org/­sql
Technical documentationorigodb.com/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHypertable Inc.Robert Friberg et alOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release20092009 infounder the name LiveDB20092014
Current release0.9.8.11, March 20163.2.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen SourceOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache 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++C#ErlangScala
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
Windows
Linux
OS X
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoUser defined using .NET types and collectionsnoyes
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.no infocan be achieved using .NETnono
Secondary indexesrestricted infoonly exact value or prefix value scansyesrestrictedno
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsC++ API
Thrift
.NET Client API
HTTP API
LINQ
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.NetC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesErlangno
Triggersnoyes infoDomain Eventsyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoclient side managed; servers are not synchronizedSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelSource-replica replicationselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynodepending on modelno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnoRole based authorizationyes, using Riak Securityno

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More resources
HypertableOrigoDBRiak KVSpark SQL
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