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DBMS > GridGain vs. Hypertable vs. Riak KV vs. Spark SQL

System Properties Comparison GridGain vs. Hypertable vs. Riak KV vs. Spark SQL

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHypertable  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteAn open source BigTable implementation based on distributed file systems such as HadoopDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value store
Relational DBMS
Wide column storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational 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
Score4.10
Rank#82  Overall
#9  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.gridgain.comspark.apache.org/­sql
Technical documentationwww.gridgain.com/­docs/­index.htmlwww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGridGain Systems, Inc.Hypertable Inc.OpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release2007200920092014
Current releaseGridGain 8.5.10.9.8.11, March 20163.2.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC++ErlangScala
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnonoyes
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 indexesyesrestricted infoonly exact value or prefix value scansrestrictedno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnonoSQL-like DML and DDL statements
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
C++ API
Thrift
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
Perl
PHP
Python
Ruby
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)noErlangno
Triggersyes (cache interceptors and events)noyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)selectable replication factor on file system levelselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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.yesno
User concepts infoAccess controlSecurity Hooks for custom implementationsnoyes, using Riak Securityno

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GridGainHypertableRiak KVSpark SQL
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