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DBMS > Datomic vs. Informix vs. Microsoft Azure Data Explorer vs. SQLite vs. Valentina Server

System Properties Comparison Datomic vs. Informix vs. Microsoft Azure Data Explorer vs. SQLite vs. Valentina Server

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonInformix  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSQLite  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataFully managed big data interactive analytics platformWidely used embeddable, in-process RDBMSObject-relational database and reports server
Primary database modelRelational DBMSRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMS infocolumn orientedRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
Document 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
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score111.41
Rank#10  Overall
#7  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitewww.datomic.comwww.ibm.com/­products/­informixazure.microsoft.com/­services/­data-explorerwww.sqlite.orgwww.valentina-db.net
Technical documentationdocs.datomic.cominformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
docs.microsoft.com/­en-us/­azure/­data-explorerwww.sqlite.org/­docs.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperCognitectIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.MicrosoftDwayne Richard HippParadigma Software
Initial release20121984201920001999
Current release1.0.7075, December 202314.10.FC5, November 2020cloud service with continuous releases3.46.0  (23 May 2024), May 20245.7.5
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infofree developer edition availablecommercialOpen Source infoPublic Domaincommercial
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, ClojureC, C++ and JavaC
Server operating systemsAll OS with a Java VMAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedserver-lessLinux
OS X
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes infodynamic column typesyes
Typing infopredefined data types such as float or dateyesyes infoSince Version 12.10 support for JSON/BSON datatypesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infonot rigid because of 'dynamic typing' concept.yes
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.noyesno
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoyesKusto Query Language (KQL), SQL subsetyes infoSQL-92 is not fully supportedyes
APIs and other access methodsRESTful HTTP APIJDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
ODBC
Supported programming languagesClojure
Java
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infoTransaction FunctionsyesYes, possible languages: KQL, Python, Rnoyes
TriggersBy using transaction functionsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infovia file-system locks
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
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 developmentyesnoyesyes
User concepts infoAccess controlnoUsers with fine-grained authentication, authorization, and auditing controlsAzure Active Directory Authenticationnofine grained access rights according to SQL-standard

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More resources
DatomicInformixMicrosoft Azure Data ExplorerSQLiteValentina Server
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