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DBMS > Datomic vs. Lovefield vs. Microsoft Azure Data Explorer vs. OceanBase vs. Virtuoso

System Properties Comparison Datomic vs. Lovefield vs. Microsoft Azure Data Explorer vs. OceanBase vs. Virtuoso

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOceanBase  Xexclude from comparisonVirtuoso  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEmbeddable relational database for web apps written in pure JavaScriptFully managed big data interactive analytics platformA distributed, high available RDBMS compatible with Oracle and MySQLVirtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedRelational DBMSDocument store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search 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
Document store
Wide column store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.66
Rank#147  Overall
#68  Relational DBMS
Score4.26
Rank#78  Overall
#13  Document stores
#4  Graph DBMS
#2  Native XML DBMS
#42  Relational DBMS
#2  RDF stores
#9  Search engines
Websitewww.datomic.comgoogle.github.io/­lovefieldazure.microsoft.com/­services/­data-exploreren.oceanbase.comvirtuoso.openlinksw.com
Technical documentationdocs.datomic.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­en-us/­azure/­data-exploreren.oceanbase.com/­docs/­oceanbase-databasedocs.openlinksw.com/­virtuoso
DeveloperCognitectGoogleMicrosoftOceanBase infopreviously Alibaba and Ant GroupOpenLink Software
Initial release20122014201920101998
Current release1.0.6735, June 20232.1.12, February 2017cloud service with continuous releases4.3.0, April 20247.2.11, September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0commercialOpen Source infoCommercial license availableOpen Source infoGPLv2, extended commercial license available
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, ClojureJavaScriptC++C
Server operating systemsAll OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedLinuxAIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesyes infoSQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type
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
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.nonoyesyesyes
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like query language infovia JavaScript builder patternKusto Query Language (KQL), SQL subsetyesyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT
Supported programming languagesClojure
Java
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoYes, possible languages: KQL, Python, RPL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible modeyes infoVirtuoso PL
TriggersBy using transaction functionsUsing read-only observersyes 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 peersnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning (by hash, key, range, range columns, list, and list columns)yes
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication using PaxosChain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
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)yes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
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 developmentyes infousing MemoryDBnoyes
User concepts infoAccess controlnonoAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardFine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
DatomicLovefieldMicrosoft Azure Data ExplorerOceanBaseVirtuoso
Specific characteristicsVirtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesPerformance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosUsed for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersBroad use across enterprises and governments including — European Union (EU) US Government...
» more
Market metricsLargest installed-base ​of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more
Licensing and pricing modelsAvailable in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more

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DatomicLovefieldMicrosoft Azure Data ExplorerOceanBaseVirtuoso
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