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DBMS > Apache Impala vs. Kdb vs. Linter vs. Milvus

System Properties Comparison Apache Impala vs. Kdb vs. Linter vs. Milvus

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonKdb  Xexclude from comparisonLinter  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopHigh performance Time Series DBMSRDBMS for high security requirementsA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSTime Series DBMS
Vector DBMS
Relational DBMSVector DBMS
Secondary database modelsDocument storeRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Websiteimpala.apache.orgkx.comlinter.rumilvus.io
Technical documentationimpala.apache.org/­impala-docs.htmlcode.kx.commilvus.io/­docs/­overview.md
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaKx Systems, a division of First Derivatives plcrelex.ru
Initial release20132000 infokdb was released 2000, kdb+ in 200319902019
Current release4.1.0, June 20223.6, May 20182.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree 32-bit versioncommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++qC and C++C++, Go
Server operating systemsLinuxLinux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesyesyes
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.noyesnono
Secondary indexesyesyes infotable attribute 'grouped'yesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (q)yesno
APIs and other access methodsJDBC
ODBC
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsyes infoproprietary syntax with the possibility to convert from PL/SQLno
Triggersnoyes infowith viewsyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno infosimilar paradigm used for internal processingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 datanonoACIDno
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosrights management via user accountsfine grained access rights according to SQL-standardRole based access control and fine grained access rights
More information provided by the system vendor
Apache ImpalaKdbLinterMilvus
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...
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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...
» 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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Apache ImpalaKdbLinterMilvus
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