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DBMS > Apache Hive vs. GridGain vs. Microsoft Azure Table Storage

System Properties Comparison Apache Hive vs. GridGain vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache Hive  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopGridGain is an in-memory computing platform, built on Apache IgniteA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score53.09
Rank#18  Overall
#12  Relational DBMS
Score1.37
Rank#154  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#70  Relational DBMS
Score3.05
Rank#84  Overall
#6  Wide column stores
Websitehive.apache.orgwww.gridgain.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.gridgain.com/­docs/­index.html
DeveloperApache Software Foundation infoinitially developed by FacebookGridGain Systems, Inc.Microsoft
Initial release201220072012
Current release3.1.3, April 2022GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial, open sourcecommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .Net, Python, REST, SQL
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
z/OS
hosted
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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
RESTful HTTP API
Supported programming languagesC++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
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)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes (replicated cache)yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
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 datanoACIDoptimistic locking
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.yesno
User concepts infoAccess controlAccess rights for users, groups and rolesRole-based access control
Security Hooks for custom implementations
Access rights based on private key authentication or shared access signatures

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More resources
Apache HiveGridGainMicrosoft Azure Table Storage
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