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DBMS > Ehcache vs. Google Cloud Datastore vs. Microsoft Azure AI Search vs. Milvus

System Properties Comparison Ehcache vs. Google Cloud Datastore vs. Microsoft Azure AI Search vs. Milvus

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSearch-as-a-service for web and mobile app developmentA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelKey-value storeDocument storeSearch engineVector DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.79
Rank#66  Overall
#8  Key-value stores
Score4.13
Rank#71  Overall
#12  Document stores
Score5.75
Rank#58  Overall
#7  Search engines
Score3.01
Rank#89  Overall
#4  Vector DBMS
Websitewww.ehcache.orgcloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­searchmilvus.io
Technical documentationwww.ehcache.org/­documentationcloud.google.com/­datastore/­docslearn.microsoft.com/­en-us/­azure/­searchmilvus.io/­docs/­overview.md
DeveloperTerracotta Inc, owned by Software AGGoogleMicrosoft
Initial release2009200820152019
Current release3.10.0, March 2022V12.4.4, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
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++, Go
Server operating systemsAll OS with a Java VMhostedhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyesVector, 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.nononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)nono
APIs and other access methodsJCachegRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIRESTful HTTP API
Supported programming languagesJava.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnousing Google App Enginenono
Triggersyes infoCache Event ListenersCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerMulti-source replication using Paxosyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing Azure authenticationRole based access control and fine grained access rights
More information provided by the system vendor
EhcacheGoogle Cloud DatastoreMicrosoft Azure AI SearchMilvus
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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More resources
EhcacheGoogle Cloud DatastoreMicrosoft Azure AI SearchMilvus
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