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DBMS > HarperDB vs. Hyprcubd vs. Ingres vs. Kinetica vs. Spark SQL

System Properties Comparison HarperDB vs. Hyprcubd vs. Ingres vs. Kinetica vs. Spark SQL

Editorial information provided by DB-Engines
NameHarperDB  Xexclude from comparisonHyprcubd  Xexclude from comparisonIngres  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Serverless Time Series DBMSWell established RDBMSFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.55
Rank#248  Overall
#38  Document stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.harperdb.iohyprcubd.com (offline)www.actian.com/­databases/­ingreswww.kinetica.comspark.apache.org/­sql
Technical documentationdocs.harperdb.io/­docsdocs.actian.com/­ingresdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHarperDBHyprcubd, Inc.Actian CorporationKineticaApache Software Foundation
Initial release20171974 infooriginally developed at University Berkely in early 1970s20122014
Current release3.1, August 202111.2, May 20227.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsGoCC, C++Scala
Server operating systemsLinux
OS X
hostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
LinuxLinux
OS X
Windows
Data schemedynamic schemayesyesyesyes
Typing infopredefined data types such as float or dateyes infoJSON data typesyes infotime, int, uint, float, stringyesyesyes
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 infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLSQL-like data manipulation statementsSQL-like query languageyesSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
gRPC (https).NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresCustom Functions infosince release 3.1noyesuser defined functionsno
Triggersnonoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterhorizontal partitioning infoIngres Star to access multiple databases simultaneouslyShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definedIngres ReplicatorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesnoyes infoMVCCyesyes
Durability infoSupport for making data persistentyes, using LMDByesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and rolestoken accessfine grained access rights according to SQL-standardAccess rights for users and roles on table levelno

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More resources
HarperDBHyprcubdIngresKineticaSpark SQL
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