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DBMS > GridGain vs. Oracle Berkeley DB vs. Riak KV vs. Spark SQL

System Properties Comparison GridGain vs. Oracle Berkeley DB vs. Riak KV vs. Spark SQL

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteWidely used in-process key-value storeDistributed, 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
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Key-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
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Score4.44
Rank#80  Overall
#9  Key-value stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.gridgain.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sql
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGridGain Systems, Inc.Oracle infooriginally developed by Sleepycat, which was acquired by OracleOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release2007199420092014
Current releaseGridGain 8.5.118.1.40, May 20203.2.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infocommercial 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, Java, C++ (depending on the Berkeley DB edition)ErlangScala
Server operating systemsLinux
OS X
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
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.yesyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesyesrestrictedno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyes infoSQL interfaced based on SQLite is availablenoSQL-like DML and DDL statements
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
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)yes infoonly for the SQL APIyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Source-replica replicationselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)noyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsnoyes, using Riak Securityno

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GridGainOracle Berkeley DBRiak KVSpark SQL
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