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DBMS > Hypertable vs. Pinecone vs. Spark SQL

System Properties Comparison Hypertable vs. Pinecone vs. Spark SQL

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonPinecone  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 managed, cloud-native vector databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.pinecone.iospark.apache.org/­sql
Technical documentationdocs.pinecone.io/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHypertable Inc.Pinecone Systems, IncApache Software Foundation
Initial release200920192014
Current release0.9.8.11, March 20163.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
hostedLinux
OS X
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or datenoString, Number, Booleanyes
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 scansno
SQL infoSupport of SQLnonoSQL-like DML and DDL statements
APIs and other access methodsC++ API
Thrift
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
PythonJava
Python
R
Scala
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
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.nono
User concepts infoAccess controlnono

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HypertablePineconeSpark SQL
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