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DBMS > GridGain vs. Hive vs. PouchDB vs. Splice Machine

System Properties Comparison GridGain vs. Hive vs. PouchDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHive  Xexclude from comparisonPouchDB  Xexclude from comparisonSplice Machine  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 HadoopJavaScript DBMS with an API inspired by CouchDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Relational DBMS
Relational DBMSDocument storeRelational DBMS
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
Score2.28
Rank#115  Overall
#21  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.gridgain.comhive.apache.orgpouchdb.comsplicemachine.com
Technical documentationwww.gridgain.com/­docs/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homepouchdb.com/­guidessplicemachine.com/­how-it-works
DeveloperGridGain Systems, Inc.Apache Software Foundation infoinitially developed by FacebookApache Software FoundationSplice Machine
Initial release2007201220122014
Current releaseGridGain 8.5.13.1.3, April 20227.1.1, June 20193.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open SourceOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaJavaScriptJava
Server operating systemsLinux
OS X
Solaris
Windows
All OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesyes infovia viewsyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsnoyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
PHP
Python
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes infouser defined functions and integration of map-reduceView functions in JavaScriptyes infoJava
Triggersyes (cache interceptors and events)noyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)selectable replication factorMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yes infoquery execution via MapReduceyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights for users, groups and rolesnoAccess rights for users, groups and roles according to SQL-standard

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GridGainHivePouchDBSplice Machine
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