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DBMS > Datomic vs. Microsoft Azure Data Explorer vs. Spark SQL vs. TimescaleDB vs. Transbase

System Properties Comparison Datomic vs. Microsoft Azure Data Explorer vs. Spark SQL vs. TimescaleDB vs. Transbase

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFully managed big data interactive analytics platformSpark SQL is a component on top of 'Spark Core' for structured data processingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMS infocolumn orientedRelational DBMSTime Series DBMSRelational DBMS
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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.datomic.comazure.microsoft.com/­services/­data-explorerspark.apache.org/­sqlwww.timescale.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.datomic.comdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCognitectMicrosoftApache Software FoundationTimescaleTransaction Software GmbH
Initial release20122019201420171987
Current release1.0.6735, June 2023cloud service with continuous releases3.5.0 ( 2.13), September 20232.15.0, May 2024Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache 2.0Open Source infoApache 2.0commercial infofree development 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.
Implementation languageJava, ClojureScalaCC and C++
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyesyes
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-typesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.noyesnoyesno
Secondary indexesyesall fields are automatically indexednoyesyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction FunctionsYes, possible languages: KQL, Python, Rnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
TriggersBy using transaction functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneSource-replica replication with hot standby and reads on replicas infoSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDyes
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
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 developmentnononono
User concepts infoAccess controlnoAzure Active Directory Authenticationnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
DatomicMicrosoft Azure Data ExplorerSpark SQLTimescaleDBTransbase
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