DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Hive vs. Kinetica vs. Yanza

System Properties Comparison Hive vs. Kinetica vs. Yanza

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonKinetica  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUsTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitehive.apache.orgwww.kinetica.comyanza.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.com
DeveloperApache Software Foundation infoinitially developed by FacebookKineticaYanza
Initial release201220122015
Current release3.1.3, April 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++
Server operating systemsAll OS with a Java VMLinuxWindows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
HTTP API
Supported programming languagesC++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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.yes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights for users and roles on table levelno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
HiveKineticaYanza
DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Apache Hive 4.0 Launches, Revolutionizing Data Management and Analysis
1 May 2024, MyChesCo

Apache Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

Elevate Your Career with In-Demand Hadoop Skills in 2024
1 May 2024, Simplilearn

provided by Google News

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

provided by Google News



Share this page

Featured Products

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Present your product here