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DBMS > GridGain vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Sphinx

System Properties Comparison GridGain vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Sphinx

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteFully managed big data interactive analytics platformExtremely fast embedded database for small devices, IoT and MobileOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value store
Relational DBMS
Relational DBMS infocolumn orientedObject oriented DBMSSearch engine
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
Time Series DBMS
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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.gridgain.comazure.microsoft.com/­services/­data-explorerobjectbox.iosphinxsearch.com
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.iosphinxsearch.com/­docs
DeveloperGridGain Systems, Inc.MicrosoftObjectBox LimitedSphinx Technologies Inc.
Initial release2007201920172001
Current releaseGridGain 8.5.1cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache License 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC and C++C++
Server operating systemsLinux
OS X
Solaris
Windows
hostedAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesno
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.yesyesno
Secondary indexesyesall fields are automatically indexedyesyes infofull-text index on all search fields
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetnoSQL-like query language (SphinxQL)
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native APIProprietary protocol
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, Rnono
Triggersyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.online/offline synchronization between client and servernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlSecurity Hooks for custom implementationsAzure Active Directory Authenticationyesno
More information provided by the system vendor
GridGainMicrosoft Azure Data ExplorerObjectBoxSphinx
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