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DBMS > Amazon CloudSearch vs. Milvus vs. PouchDB vs. RocksDB

System Properties Comparison Amazon CloudSearch vs. Milvus vs. PouchDB vs. RocksDB

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonMilvus  Xexclude from comparisonPouchDB  Xexclude from comparisonRocksDB  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudA DBMS designed for efficient storage of vector data and vector similarity searchesJavaScript DBMS with an API inspired by CouchDBEmbeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelSearch engineVector DBMSDocument storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score3.65
Rank#85  Overall
#11  Key-value stores
Websiteaws.amazon.com/­cloudsearchmilvus.iopouchdb.comrocksdb.org
Technical documentationdocs.aws.amazon.com/­cloudsearchmilvus.io/­docs/­overview.mdpouchdb.com/­guidesgithub.com/­facebook/­rocksdb/­wiki
DeveloperAmazonApache Software FoundationFacebook, Inc.
Initial release2012201920122013
Current release2.3.4, January 20247.1.1, June 20198.11.4, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open SourceOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnonono
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++, GoJavaScriptC++
Server operating systemshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
server-less, requires a JavaScript environment (browser, Node.js)Linux
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringnono
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.nonono
Secondary indexesyes infoall search fields are automatically indexednoyes infovia viewsno
SQL infoSupport of SQLnononono
APIs and other access methodsHTTP APIRESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
C++ API
Java API
Supported programming languagesC++
Go
Java
JavaScript (Node.js)
Python
JavaScriptC
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresnonoView functions in JavaScriptno
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingSharding infowith a proxy-based framework, named couchdb-loungehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlauthentication via encrypted signaturesRole based access control and fine grained access rightsnono
More information provided by the system vendor
Amazon CloudSearchMilvusPouchDBRocksDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesSpeedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon CloudSearchMilvusPouchDBRocksDB
DB-Engines blog posts

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

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Recent citations in the news

Amazon CloudSearch – Start Searching in One Hour for Less Than $100 / Month | Amazon Web Services
12 April 2012, AWS Blog

Is Amazon CloudSearch superior to do-it-yourself search tools?
24 January 2014, TechTarget

Amazon CloudSearch – Even Better Searching for Less Than $100/Month | Amazon Web Services
24 March 2014, AWS Blog

Amazon Takes On Google And Microsoft With CloudSearch
16 April 2012, Forbes

Searching CloudTrail Logs Easily with Amazon CloudSearch | AWS Startups Blog
21 October 2014, AWS Blog

provided by Google News

What Is Milvus Vector Database?
6 October 2023, The New Stack

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Cloud boosts vector database performance
31 January 2024, InfoWorld

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Building an Offline First App with PouchDB — SitePoint
10 March 2014, SitePoint

Getting Started with PouchDB Client-Side JavaScript Database — SitePoint
7 September 2016, SitePoint

3 Reasons To Think Offline First
22 March 2017, IBM

Offline-first web and mobile apps: Top frameworks and components
22 January 2019, TechBeacon

Create Offline Web Apps Using Service Workers & PouchDB — SitePoint
7 March 2017, SitePoint

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Did Rockset Just Solve Real-Time Analytics?
25 August 2021, Datanami

Meta’s Velox Means Database Performance Is Not Subject To Interpretation
31 August 2022, The Next Platform

Linux 6.9 Drives AMD 4th Gen EPYC Performance Even Higher For Some Workloads
29 March 2024, Phoronix

Power your Kafka Streams application with Amazon MSK and AWS Fargate | Amazon Web Services
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