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

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

Editorial information provided by DB-Engines
NameH2  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMilvus  Xexclude from comparisonSpeedb  Xexclude from comparison
DescriptionFull-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 searchesAn embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB
Primary database modelRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedVector DBMSKey-value store
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
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
Score0.21
Rank#315  Overall
#45  Key-value stores
Websitewww.h2database.comwww.marklogic.comazure.microsoft.com/­services/­data-explorermilvus.iowww.speedb.io
Technical documentationwww.h2database.com/­html/­main.htmldocs.marklogic.comdocs.microsoft.com/­en-us/­azure/­data-explorermilvus.io/­docs/­overview.md
DeveloperThomas MuellerMarkLogic Corp.MicrosoftSpeedb
Initial release20052001201920192020
Current release2.2.220, July 202311.0, December 2022cloud service with continuous releases2.3.4, January 2024
License infoCommercial or Open SourceOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercial inforestricted free version is availablecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0; 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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJavaC++C++, GoC++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
Windows
Data schemeyesschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)schema-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-typesVector, Numeric and Stringno
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.noyesyesnono
Secondary indexesyesyesall fields are automatically indexednono
SQL infoSupport of SQLyesyes infoSQL92Kusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
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 languagesJavaC
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
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresJava Stored Procedures and User-Defined Functionsyes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, Rnono
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesWith 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.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infocan act as a resource manager in an XA/JTA transactionnonoyes
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, with Range Indexesnoyesyes
User concepts infoAccess controlfine 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 rightsno
More information provided by the system vendor
H2MarkLogicMicrosoft Azure Data ExplorerMilvusSpeedb
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Speedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Speedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» 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
Open source - Speedb OSS is released under an Apache license and can be found on...
» more

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H2MarkLogicMicrosoft Azure Data ExplorerMilvusSpeedb
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