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DBMS > Datomic vs. Google Cloud Datastore vs. Milvus vs. PouchDB

System Properties Comparison Datomic vs. Google Cloud Datastore vs. Milvus vs. PouchDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMilvus  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA DBMS designed for efficient storage of vector data and vector similarity searchesJavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSDocument storeVector DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Websitewww.datomic.comcloud.google.com/­datastoremilvus.iopouchdb.com
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsmilvus.io/­docs/­overview.mdpouchdb.com/­guides
DeveloperCognitectGoogleApache Software Foundation
Initial release2012200820192012
Current release1.0.6735, June 20232.3.4, January 20247.1.1, June 2019
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 languageJava, ClojureC++, GoJavaScript
Server operating systemsAll OS with a Java VMhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereVector, 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.nononono
Secondary indexesyesyesnoyes infovia views
SQL infoSupport of SQLnoSQL-like query language (GQL)nono
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App EnginenoView functions in JavaScript
TriggersBy using transaction functionsCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using PaxosMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based access control and fine grained access rightsno
More information provided by the system vendor
DatomicGoogle Cloud DatastoreMilvusPouchDB
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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DatomicGoogle Cloud DatastoreMilvusPouchDB
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