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DBMS > Apache Druid vs. Blueflood vs. Microsoft Azure Data Explorer vs. Milvus vs. SwayDB

System Properties Comparison Apache Druid vs. Blueflood vs. Microsoft Azure Data Explorer vs. Milvus vs. SwayDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBlueflood  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMilvus  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataScalable TimeSeries DBMS based on CassandraFully managed big data interactive analytics platformA DBMS designed for efficient storage of vector data and vector similarity searchesAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMS infocolumn orientedVector DBMSKey-value store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitedruid.apache.orgblueflood.ioazure.microsoft.com/­services/­data-explorermilvus.ioswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designgithub.com/­rax-maas/­blueflood/­wikidocs.microsoft.com/­en-us/­azure/­data-explorermilvus.io/­docs/­overview.md
DeveloperApache Software Foundation and contributorsRackspaceMicrosoftSimer Plaha
Initial release20122013201920192018
Current release29.0.1, April 2024cloud service with continuous releases2.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0commercialOpen Source infoApache Version 2.0Open Source infoGNU Affero GPL V3.0
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 languageJavaJavaC++, GoScala
Server operating systemsLinux
OS X
Unix
Linux
OS X
hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyes infoschema-less columns are supportedpredefined schemeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesVector, 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.nonoyesnono
Secondary indexesyesnoall fields are automatically indexednono
SQL infoSupport of SQLSQL for queryingnoKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP RESTMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
JavaScript (Node.js)
Python
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rnono
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoAtomic execution of operations
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.nononoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAzure Active Directory AuthenticationRole based access control and fine grained access rightsno
More information provided by the system vendor
Apache DruidBluefloodMicrosoft Azure Data ExplorerMilvusSwayDB
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...
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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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More resources
Apache DruidBluefloodMicrosoft Azure Data ExplorerMilvusSwayDB
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