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DBMS > Apache Druid vs. GridGain vs. Realm vs. Riak KV

System Properties Comparison Apache Druid vs. GridGain vs. Realm vs. Riak KV

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGridGain  Xexclude from comparisonRealm  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGridGain is an in-memory computing platform, built on Apache IgniteA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataDistributed, fault tolerant key-value store
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Document storeKey-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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitedruid.apache.orgwww.gridgain.comrealm.io
Technical documentationdruid.apache.org/­docs/­latest/­designwww.gridgain.com/­docs/­index.htmlrealm.io/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation and contributorsGridGain Systems, Inc.Realm, acquired by MongoDB in May 2019OpenSource, formerly Basho Technologies
Initial release2012200720142009
Current release29.0.1, April 2024GridGain 8.5.13.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen SourceOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetErlang
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Data schemeyes infoschema-less columns are supportedyesyesschema-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.noyesnono
Secondary indexesyesyesyesrestricted
SQL infoSupport of SQLSQL for queryingANSI-99 for query and DML statements, subset of DDLnono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Native Erlang Interface
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Java infowith Android only
Objective-C
React Native
Swift
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 proceduresnoyes (compute grid and cache interceptors can be used instead)no inforuns within the applications so server-side scripts are unnecessaryErlang
Triggersnoyes (cache interceptors and events)yes infoChange Listenersyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingnoneSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes (replicated cache)noneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)noyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.noyesyes infoIn-Memory realm
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity Hooks for custom implementationsyesyes, using Riak Security

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Apache DruidGridGainRealmRiak KV
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