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DBMS > GridGain vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. Sphinx vs. XTDB

System Properties Comparison GridGain vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. Sphinx vs. XTDB

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSphinx  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteFully managed big data interactive analytics platformMicrosofts flagship relational DBMSOpen source search engine for searching in data from different sources, e.g. relational databasesA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelKey-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMSSearch engineDocument 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
Document store
Graph DBMS
Spatial 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
Score821.56
Rank#3  Overall
#3  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.18
Rank#332  Overall
#46  Document stores
Websitewww.gridgain.comazure.microsoft.com/­services/­data-explorerwww.microsoft.com/­en-us/­sql-serversphinxsearch.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerlearn.microsoft.com/­en-US/­sql/­sql-serversphinxsearch.com/­docswww.xtdb.com/­docs
DeveloperGridGain Systems, Inc.MicrosoftMicrosoftSphinx Technologies Inc.Juxt Ltd.
Initial release20072019198920012019
Current releaseGridGain 8.5.1cloud service with continuous releasesSQL Server 2022, November 20223.5.1, February 20231.19, September 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageJava, C++, .NetC++C++Clojure
Server operating systemsLinux
OS X
Solaris
Windows
hostedLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyesschema-free
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-typesyesnoyes, extensible-data-notation format
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.yesyesyesno
Secondary indexesyesall fields are automatically indexedyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetyesSQL-like query language (SphinxQL)limited SQL, making use of Apache Calcite
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
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Proprietary protocolHTTP REST
JDBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Clojure
Java
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, RTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javanono
Triggersyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicetables can be distributed across several files (horizontal partitioning); sharding through federationSharding infoPartitioning is done manually, search queries against distributed index is supportednone
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.yes, but depending on the SQL-Server Editionnoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlSecurity Hooks for custom implementationsAzure Active Directory Authenticationfine grained access rights according to SQL-standardno

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