DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > LMDB vs. Milvus vs. Netezza vs. Tkrzw

System Properties Comparison LMDB vs. Milvus vs. Netezza vs. Tkrzw

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameLMDB  Xexclude from comparisonMilvus  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionA high performant, light-weight, embedded key-value database libraryA DBMS designed for efficient storage of vector data and vector similarity searchesData warehouse and analytics appliance part of IBM PureSystemsA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value storeVector DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#125  Overall
#21  Key-value stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.symas.com/­symas-embedded-database-lmdbmilvus.iowww.ibm.com/­products/­netezzadbmx.net/­tkrzw
Technical documentationwww.lmdb.tech/­docmilvus.io/­docs/­overview.md
DeveloperSymasIBMMikio Hirabayashi
Initial release2011201920002020
Current release0.9.32, January 20242.3.4, January 20240.9.3, August 2020
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2.0commercialOpen 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 languageCC++, GoC++
Server operating systemsLinux
Unix
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux infoincluded in applianceLinux
macOS
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or dateVector, Numeric and Stringyesno
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.nonono
Secondary indexesnonoyes
SQL infoSupport of SQLnonoyesno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
OLE DB
Supported programming languages.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnonoyesno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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.yesyesyes infousing specific database classes
User concepts infoAccess controlnoRole based access control and fine grained access rightsUsers with fine-grained authorization conceptno
More information provided by the system vendor
LMDBMilvusNetezza infoAlso called PureData System for Analytics by IBMTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
LMDBMilvusNetezza infoAlso called PureData System for Analytics by IBMTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Automating SAP S/4HANA Migration with IT-Conductor, BGP Managed Services, and AWS | Amazon Web Services
22 August 2023, AWS Blog

The Tom Brady Data Biography
8 September 2023, StatsBomb

The Lightning Memory-mapped Database
2 March 2016, InfoQ.com

Akamai launches managed database service – Blocks and Files
25 April 2022, Blocks and Files

Connecting the worlds of metabolomics databases
15 June 2021, Medical Xpress

provided by Google News

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, IBM

provided by Google News

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

Tackling AI's data challenges with IBM databases on AWS
14 March 2024, IBM

provided by Google News



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Present your product here