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DBMS > Geode vs. Hive vs. Spark SQL

System Properties Comparison Geode vs. Hive vs. Spark SQL

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonHive  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesdata warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#133  Overall
#23  Key-value stores
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitegeode.apache.orghive.apache.orgspark.apache.org/­sql
Technical documentationgeode.apache.org/­docscwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release200220122014
Current release1.1, February 20173.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScala
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredAll OS with a Java VMLinux
OS X
Windows
Data schemeschema-freeyesyes
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.nono
Secondary indexesnoyesno
SQL infoSupport of SQLSQL-like query language (OQL)SQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reduceno
Triggersyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodenono
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 per client and object definableAccess rights for users, groups and rolesno

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