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DBMS > Ehcache vs. Microsoft Azure Data Explorer vs. Milvus vs. Tibero vs. Weaviate

System Properties Comparison Ehcache vs. Microsoft Azure Data Explorer vs. Milvus vs. Tibero vs. Weaviate

Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMilvus  Xexclude from comparisonTibero  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsFully managed big data interactive analytics platformA DBMS designed for efficient storage of vector data and vector similarity searchesA secure RDBMS, designed for easy portability from OracleAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelKey-value storeRelational DBMS infocolumn orientedVector DBMSRelational DBMSVector 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score1.78
Rank#140  Overall
#64  Relational DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.ehcache.orgazure.microsoft.com/­services/­data-explorermilvus.ious.tmaxsoft.com/­products/­tiberogithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationwww.ehcache.org/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorermilvus.io/­docs/­overview.mdtechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.htmlweaviate.io/­developers/­weaviate
DeveloperTerracotta Inc, owned by Software AGMicrosoftTmaxSoftWeaviate B.V.
Initial release20092019201920032019
Current release3.10.0, March 2022cloud service with continuous releases2.3.4, January 20246, April 20151.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache Version 2.0commercialOpen Source infocommercial license available with Weaviate Enterprise
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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJavaC++, GoC and AssemblerGo
Server operating systemsAll OS with a Java VMhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
AIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesyes, maps to GraphQL interface
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-typesVector, Numeric and Stringyesyes infostring, int, float, geo point, date, cross reference, fuzzy references
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 indexesnoall fields are automatically indexednoyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetnoyesGraphQL is used as query language
APIs and other access methodsJCacheMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesJava.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RnoPersistent Stored Procedure (PSM)no
Triggersyes infoCache Event Listenersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning infoby range, hash, list or compositeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serveryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno infoplanned for next versionyes
User concepts infoAccess controlnoAzure Active Directory AuthenticationRole based access control and fine grained access rightsfine grained access rights according to SQL-standard (SQL 92, SQL 99)API Keys
OpenID Connect Discovery
More information provided by the system vendor
EhcacheMicrosoft Azure Data ExplorerMilvusTiberoWeaviate
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
As a database supporting the development of generative AI and semantic search applications...
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Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
All companies that have data. ​
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more
Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
EhcacheMicrosoft Azure Data ExplorerMilvusTiberoWeaviate
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