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DBMS > Apache Druid vs. Google Cloud Bigtable vs. Kdb vs. Milvus

System Properties Comparison Apache Druid vs. Google Cloud Bigtable vs. Kdb vs. Milvus

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Bigtable  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 dataGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.High performance Time Series DBMSA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Wide column store
Time 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
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score7.73
Rank#45  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score3.01
Rank#89  Overall
#4  Vector DBMS
Websitedruid.apache.orgcloud.google.com/­bigtablekx.commilvus.io
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­bigtable/­docscode.kx.commilvus.io/­docs/­overview.md
DeveloperApache Software Foundation and contributorsGoogleKx 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 servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJavaqC++, Go
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
Solaris
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyes infoschema-less columns are supportedschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesVector, 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 indexesyesnoyes infotable attribute 'grouped'no
SQL infoSupport of SQLSQL for queryingnoSQL-like query language (q)no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonouser 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 enginesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-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 consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnono
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 systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsRole based access control and fine grained access rights
More information provided by the system vendor
Apache DruidGoogle Cloud BigtableKdbMilvus
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...
» more
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...
» more
RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
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 DruidGoogle Cloud BigtableKdbMilvus
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