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DBMS > Datomic vs. H2 vs. MarkLogic vs. Microsoft Azure Data Explorer vs. Milvus

System Properties Comparison Datomic vs. H2 vs. MarkLogic vs. Microsoft Azure Data Explorer vs. Milvus

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonH2  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Operational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platformA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedVector DBMS
Secondary database modelsSpatial DBMSDocument 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitewww.datomic.comwww.h2database.comwww.marklogic.comazure.microsoft.com/­services/­data-explorermilvus.io
Technical documentationdocs.datomic.comwww.h2database.com/­html/­main.htmldocs.marklogic.comdocs.microsoft.com/­en-us/­azure/­data-explorermilvus.io/­docs/­overview.md
DeveloperCognitectThomas MuellerMarkLogic Corp.Microsoft
Initial release20122005200120192019
Current release1.0.6735, June 20232.2.220, July 202311.0, December 2022cloud service with continuous releases2.3.4, January 2024
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercial inforestricted free version is availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJava, ClojureJavaC++C++, Go
Server operating systemsAll OS with a Java VMAll OS with a Java VMLinux
OS X
Windows
hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesyesschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesVector, Numeric and String
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.nonoyesyesno
Secondary indexesyesyesyesall fields are automatically indexedno
SQL infoSupport of SQLnoyesyes infoSQL92Kusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesClojure
Java
JavaC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoTransaction FunctionsJava Stored Procedures and User-Defined Functionsyes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, Rno
TriggersBy using transaction functionsyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersWith clustering: 2 database servers on different computers operate on identical copies of a databaseyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infocan act as a resource manager in an XA/JTA transactionnono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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 developmentyesyes, with Range Indexesnoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardRole-based access control at the document and subdocument levelsAzure Active Directory AuthenticationRole based access control and fine grained access rights
More information provided by the system vendor
DatomicH2MarkLogicMicrosoft Azure Data ExplorerMilvus
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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DatomicH2MarkLogicMicrosoft Azure Data ExplorerMilvus
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