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DBMS > Apache IoTDB vs. Couchbase vs. Microsoft Azure Synapse Analytics vs. Milvus vs. Spark SQL

System Properties Comparison Apache IoTDB vs. Couchbase vs. Microsoft Azure Synapse Analytics vs. Milvus vs. Spark SQL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCouchbase infoOriginally called Membase  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile databaseElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searchesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSDocument storeRelational DBMSVector DBMSRelational DBMS
Secondary database modelsKey-value store infooriginating from the former Membase product and supporting the Memcached protocol
Spatial DBMS infousing the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score16.59
Rank#36  Overall
#5  Document stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgwww.couchbase.comazure.microsoft.com/­services/­synapse-analyticsmilvus.iospark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.couchbase.comdocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationCouchbase, Inc.MicrosoftApache Software Foundation
Initial release20182011201620192014
Current release1.1.0, April 2023Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 20232.3.4, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBusiness Source License (BSL 1.1); Commercial licenses also availablecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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, C++, Go and ErlangC++C++, GoScala
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesVector, Numeric and Stringyes
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 indexesyesyesyesnono
SQL infoSupport of SQLSQL-like query languageSQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use casesyesnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data
ADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
Go
Java
JavaScript infoNode.js
Kotlin
PHP
Python
Ruby
Scala
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesFunctions and timers in JavaScript and UDFs in Java, Python, SQL++Transact SQLnono
Triggersyesyes infovia the TAP protocolnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic ShardingSharding, horizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication infoincluding cross data center replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency infoselectable on a per-operation basis
Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesyes infoEphemeral bucketsyesno
User concepts infoAccess controlyesUser and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.yesRole based access control and fine grained access rightsno
More information provided by the system vendor
Apache IoTDBCouchbase infoOriginally called MembaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusSpark SQL
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
Apache IoTDBCouchbase infoOriginally called MembaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusSpark SQL
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