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

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

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGridGain is an in-memory computing platform, built on Apache IgniteFully managed big data interactive analytics platformMicrosofts flagship relational DBMSA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMSDocument 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
Score1.66
Rank#144  Overall
#66  Relational DBMS
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
Score0.18
Rank#332  Overall
#46  Document stores
Websitewww.datomic.comwww.gridgain.comazure.microsoft.com/­services/­data-explorerwww.microsoft.com/­en-us/­sql-servergithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationdocs.datomic.comwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerlearn.microsoft.com/­en-US/­sql/­sql-serverwww.xtdb.com/­docs
DeveloperCognitectGridGain Systems, Inc.MicrosoftMicrosoftJuxt Ltd.
Initial release20122007201919892019
Current release1.0.6735, June 2023GridGain 8.5.1cloud service with continuous releasesSQL Server 2022, November 20221.19, September 2021
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercial inforestricted free version is availableOpen Source infoMIT License
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.
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, ClojureJava, C++, .NetC++Clojure
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
hostedLinux
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesschema-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-typesyesyes, 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.noyesyesyesno
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetyeslimited SQL, making use of Apache Calcite
APIs and other access methodsRESTful HTTP APIHDFS 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)
HTTP REST
JDBC
Supported programming languagesClojure
Java
C#
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
Clojure
Java
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes (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) Javano
TriggersBy using transaction functionsyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoImplicit feature of the cloud servicetables can be distributed across several files (horizontal partitioning); sharding through federationnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, but depending on the SQL-Server Editionyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (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 ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes, 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.yes inforecommended only for testing and developmentyesnoyes
User concepts infoAccess controlnoSecurity Hooks for custom implementationsAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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DatomicGridGainMicrosoft Azure Data ExplorerMicrosoft SQL ServerXTDB infoformerly named Crux
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