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DBMS > Apache Druid vs. EsgynDB vs. Kdb vs. Milvus

System Properties Comparison Apache Druid vs. EsgynDB vs. Kdb vs. Milvus

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEsgynDB  Xexclude from comparisonKdb  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHigh performance Time Series DBMSA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMS
Vector DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score7.73
Rank#45  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score3.01
Rank#89  Overall
#4  Vector DBMS
Websitedruid.apache.orgwww.esgyn.cnkx.commilvus.io
Technical documentationdruid.apache.org/­docs/­latest/­designcode.kx.commilvus.io/­docs/­overview.md
DeveloperApache Software Foundation and contributorsEsgynKx Systems, a division of First Derivatives plc
Initial release201220152000 infokdb was released 2000, kdb+ in 20032019
Current release30.0.0, June 20243.6, May 20182.4.4, May 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infofree 32-bit versionOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
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++, JavaqC++, Go
Server operating systemsLinux
OS X
Unix
LinuxLinux
OS X
Solaris
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyesyesVector, Numeric and String
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.nonoyesno
Secondary indexesyesyesyes infotable attribute 'grouped'no
SQL infoSupport of SQLSQL for queryingyesSQL-like query language (q)no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoJava Stored Proceduresuser defined functionsno
Triggersnonoyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication between multi datacentersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardrights management via user accountsRole based access control and fine grained access rights
More information provided by the system vendor
Apache DruidEsgynDBKdbMilvus
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Milvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Highly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
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RAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
As of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsupon request
» more
Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
Apache DruidEsgynDBKdbMilvus
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