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DBMS > GridGain vs. Ignite vs. Microsoft Azure Data Explorer vs. Riak KV vs. TerarkDB

System Properties Comparison GridGain vs. Ignite vs. Microsoft Azure Data Explorer vs. Riak KV vs. TerarkDB

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformDistributed, fault tolerant key-value storeA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelKey-value store
Relational DBMS
Key-value store
Relational DBMS
Relational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesKey-value store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score0.08
Rank#367  Overall
#56  Key-value stores
Websitewww.gridgain.comignite.apache.orgazure.microsoft.com/­services/­data-explorergithub.com/­bytedance/­terarkdb
Technical documentationwww.gridgain.com/­docs/­index.htmlapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latestbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperGridGain Systems, Inc.Apache Software FoundationMicrosoftOpenSource, formerly Basho TechnologiesByteDance, originally Terark
Initial release20072015201920092016
Current releaseGridGain 8.5.1Apache Ignite 2.6cloud service with continuous releases3.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache version 2, commercial enterprise editioncommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC++, Java, .NetErlangC++
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnono
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.yesyesyesnono
Secondary indexesyesyesall fields are automatically indexedrestrictedno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
C++ API
Java API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
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
C++
Java
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, RErlangno
Triggersyes (cache interceptors and events)yes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"none
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlSecurity Hooks for custom implementationsSecurity Hooks for custom implementationsAzure Active Directory Authenticationyes, using Riak Securityno

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More resources
GridGainIgniteMicrosoft Azure Data ExplorerRiak KVTerarkDB
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