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DBMS > GridGain vs. Hive vs. Microsoft Azure Synapse Analytics vs. Riak KV

System Properties Comparison GridGain vs. Hive vs. Microsoft Azure Synapse Analytics vs. Riak KV

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache Ignitedata warehouse software for querying and managing large distributed datasets, built on HadoopElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerDistributed, fault tolerant key-value store
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitewww.gridgain.comhive.apache.orgazure.microsoft.com/­services/­synapse-analytics
Technical documentationwww.gridgain.com/­docs/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­azure/­synapse-analyticswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperGridGain Systems, Inc.Apache Software Foundation infoinitially developed by FacebookMicrosoftOpenSource, formerly Basho Technologies
Initial release2007201220162009
Current releaseGridGain 8.5.13.1.3, April 20223.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaC++Erlang
Server operating systemsLinux
OS X
Solaris
Windows
All OS with a Java VMhostedLinux
OS X
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.yesnono
Secondary indexesyesyesyesrestricted
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsyesno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
HTTP API
Native Erlang Interface
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
PHP
Python
C#
Java
PHP
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes infouser defined functions and integration of map-reduceTransact SQLErlang
Triggersyes (cache interceptors and events)nonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)selectable replication factoryesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights for users, groups and rolesyesyes, using Riak Security

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More resources
GridGainHiveMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRiak KV
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