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DBMS > Hypertable vs. OrigoDB vs. Rockset vs. Spark SQL

System Properties Comparison Hypertable vs. OrigoDB vs. Rockset vs. Spark SQL

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonOrigoDB  Xexclude from comparisonRockset  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 databaseA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeDocument store
Object oriented DBMS
Document storeRelational DBMS
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteorigodb.comrockset.comspark.apache.org/­sql
Technical documentationorigodb.com/­docsdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHypertable Inc.Robert Friberg et alRocksetApache Software Foundation
Initial release20092009 infounder the name LiveDB20192014
Current release0.9.8.11, March 20163.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen SourcecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#C++Scala
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoUser defined using .NET types and collectionsdynamic typingyes
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 .NETno infoingestion from XML files supportedno
Secondary indexesrestricted infoonly exact value or prefix value scansyesall fields are automatically indexedno
SQL infoSupport of SQLnonoRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsC++ API
Thrift
.NET Client API
HTTP API
LINQ
HTTP RESTJDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.NetGo
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyes infoDomain Eventsnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoclient side managed; servers are not synchronizedAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynodepending on modelnono
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 authorizationAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
HypertableOrigoDBRocksetSpark SQL
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