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DBMS > CouchDB vs. Microsoft Azure Synapse Analytics vs. Milvus vs. ObjectBox vs. Spark SQL

System Properties Comparison CouchDB vs. Microsoft Azure Synapse Analytics vs. Milvus vs. ObjectBox vs. Spark SQL

Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparisonObjectBox  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searchesExtremely fast embedded database for small devices, IoT and MobileSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSVector DBMSObject oriented DBMSRelational DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extensionTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.30
Rank#47  Overall
#7  Document stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitecouchdb.apache.orgazure.microsoft.com/­services/­synapse-analyticsmilvus.ioobjectbox.iospark.apache.org/­sql
Technical documentationdocs.couchdb.org/­en/­stabledocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.mddocs.objectbox.iospark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerMicrosoftObjectBox LimitedApache Software Foundation
Initial release20052016201920172014
Current release3.3.3, December 20232.3.4, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen Source infoApache Version 2.0Open Source infoApache License 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Zilliz Cloud – Cloud-native service for Milvus
Implementation languageErlangC++C++, GoC and C++Scala
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Android
iOS
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesVector, Numeric and Stringyesyes
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.nonononono
Secondary indexesyes infovia viewsyesnoyesno
SQL infoSupport of SQLnoyesnonoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
JDBC
ODBC
RESTful HTTP APIProprietary native APIJDBC
ODBC
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresView functions in JavaScriptTransact SQLnonono
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0Sharding, horizontal partitioningShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesonline/offline synchronization between client and servernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights for users can be defined per databaseyesRole based access control and fine grained access rightsyesno
More information provided by the system vendor
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusObjectBoxSpark SQL
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
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Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
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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...
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