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DBMS > DolphinDB vs. Milvus vs. Netezza vs. Solr

System Properties Comparison DolphinDB vs. Milvus vs. Netezza vs. Solr

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Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonMilvus  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A DBMS designed for efficient storage of vector data and vector similarity searchesData warehouse and analytics appliance part of IBM PureSystemsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSVector DBMSRelational DBMSSearch engine
Secondary database modelsRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.dolphindb.commilvus.iowww.ibm.com/­products/­netezzasolr.apache.org
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlmilvus.io/­docs/­overview.mdsolr.apache.org/­resources.html
DeveloperDolphinDB, IncIBMApache Software Foundation
Initial release2018201920002006
Current releasev2.00.4, January 20222.3.4, January 20249.6.0, April 2024
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2
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 languageC++C++, GoJava
Server operating systemsLinux
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux infoincluded in applianceAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesyes infosupports customizable data types and automatic typing
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.nonoyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoyesSolr Parallel SQL Interface
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
RESTful HTTP APIJDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesnoyesJava plugins
Triggersnononoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDoptimistic locking
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
User concepts infoAccess controlAdministrators, Users, GroupsRole based access control and fine grained access rightsUsers with fine-grained authorization conceptyes
More information provided by the system vendor
DolphinDBMilvusNetezza infoAlso called PureData System for Analytics by IBMSolr
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

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More resources
DolphinDBMilvusNetezza infoAlso called PureData System for Analytics by IBMSolr
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