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DBMS > Drizzle vs. HarperDB vs. Hive vs. Kinetica

System Properties Comparison Drizzle vs. HarperDB vs. Hive vs. Kinetica

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHarperDB  Xexclude from comparisonHive  Xexclude from comparisonKinetica  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A distributed database focused on speed and ease of use. It has an intuitive REST API, and supports NoSQL and SQL including joins. HarperDB leverages standard interfaces, and users can be up and running in minutes.data warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.59
Rank#224  Overall
#34  Document stores
Score83.45
Rank#15  Overall
#10  Relational DBMS
Score0.74
Rank#202  Overall
#97  Relational DBMS
Websiteharperdb.iohive.apache.orgwww.kinetica.com
Technical documentationharperdb.io/­developers/­documentation/­overviewcwiki.apache.org/­confluence/­display/­Hive/­Homewww.kinetica.com/­docs
DeveloperDrizzle project, originally started by Brian AkerHarperDBApache Software Foundation infoinitially developed by FacebookKinetica
Initial release2008201720122012
Current release7.2.4, September 20123.1, August 20213.1.2, August 20197.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercial infofree community edition availableOpen Source infoApache Version 2commercial
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.
HarperDB Cloud: Get To Market Faster, For Less Money Using Our Built-in API.
Implementation languageC++Node.jsJavaC, C++
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
All OS with a Java VMLinux
Data schemeyesdynamic schemayesyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like data manipulation statementsSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
.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
PHP
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1yes infouser defined functions and integration of map-reduceuser defined functions
Triggersno infohooks for callbacks inside the server can be used.nonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infothe nodes on which a table resides can be definedselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAM
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and rolesAccess rights for users, groups and rolesAccess rights for users and roles on table level
More information provided by the system vendor
DrizzleHarperDBHiveKinetica
Specific characteristicsHarperDB is the first distributed database with hybrid SQL & NoSQL functionality...
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Native and fully vectorized database across both GPUs and CPUs, with memory first...
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Competitive advantagesBy combining the functionality of the best SQL, NoSQL, and NewSQL products on the...
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Best in class geospatial and temporal analytics. Lockless architecture provides real-time...
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Typical application scenariosUse cases where HarperDB is a better fit than other solutions include: Rapid app...
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Any application requiring (1) real time insights, (2) time series analysis (3) geospatial...
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Key customersA few highlighted customers include: US Army, US Airforce, Chelan PUD, TATA, & Lumen....
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Citibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
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Market metrics6,800 + npm downloads 1,600 + on Docker Hub 2,600 + cloud & local signups
» more
The largest IoT deployment in the world, NORAD, runs on Kinetica.
» more
Licensing and pricing modelsHarperDB follows a freemium/premium model . A database is only as powerful as it...
» more
Always Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
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More resources
DrizzleHarperDBHiveKinetica
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