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DBMS > Hive vs. Ignite vs. Yanza

System Properties Comparison Hive vs. Ignite vs. Yanza

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonIgnite  Xexclude from comparisonYanza  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Time Series DBMS for IoT Applications
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score79.69
Rank#14  Overall
#9  Relational DBMS
Score4.93
Rank#71  Overall
#10  Key-value stores
#40  Relational DBMS
Score0.00
Rank#350  Overall
#31  Time Series DBMS
Websitehive.apache.orgignite.apache.orgyanza.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docs
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software FoundationYanza
Initial release201220152015
Current release3.1.2, August 2019Apache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercial 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++, Java, .Net
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
Windows
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.yesno
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Supported programming languagesC++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes (cache interceptors and events)yes 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 factoryes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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
User concepts infoAccess controlAccess rights for users, groups and rolesSecurity Hooks for custom implementationsno

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HiveIgniteYanza
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