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DBMS > InterSystems Caché vs. Microsoft Access vs. Microsoft Azure Data Explorer vs. Microsoft Azure Synapse Analytics vs. Milvus

System Properties Comparison InterSystems Caché vs. Microsoft Access vs. Microsoft Azure Data Explorer vs. Microsoft Azure Synapse Analytics vs. Milvus

Editorial information provided by DB-Engines
NameInterSystems Caché  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionA multi-model DBMS and application serverMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Fully managed big data interactive analytics platformElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedRelational DBMSVector DBMS
Secondary database modelsDocument storeDocument 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
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Websitewww.intersystems.com/­products/­cachewww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­services/­synapse-analyticsmilvus.io
Technical documentationdocs.intersystems.comdeveloper.microsoft.com/­en-us/­accessdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.md
DeveloperInterSystemsMicrosoftMicrosoftMicrosoft
Initial release19971992201920162019
Current release2018.1.4, May 20201902 (16.0.11328.20222), March 2019cloud service with continuous releases2.3.4, January 2024
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
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 languageC++C++C++, Go
Server operating systemsAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Windows infoNot a real database server, but making use of DLLshostedhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemedepending on used data modelyesFixed schema with schema-less datatypes (dynamic)yes
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-typesyesVector, 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.yesyesnono
Secondary indexesyesyesall fields are automatically indexedyesno
SQL infoSupport of SQLyesyes infobut not compliant to any SQL standardKusto Query Language (KQL), SQL subsetyesno
APIs and other access methods.NET Client API
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Java
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesyes infosince Access 2010 using the ACE-engineYes, possible languages: KQL, Python, RTransact SQLno
Triggersyesyes infosince Access 2010 using the ACE-engineyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
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 ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesyesnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infobut no files for transaction loggingnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users, groups and rolesno infoa simple user-level security was built in till version Access 2003Azure Active Directory AuthenticationyesRole based access control and fine grained access rights
More information provided by the system vendor
InterSystems CachéMicrosoft AccessMicrosoft Azure Data ExplorerMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvus
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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InterSystems CachéMicrosoft AccessMicrosoft Azure Data ExplorerMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvus
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