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DBMS > Milvus vs. OrigoDB vs. Splice Machine vs. YDB

System Properties Comparison Milvus vs. OrigoDB vs. Splice Machine vs. YDB

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Editorial information provided by DB-Engines
NameMilvus  Xexclude from comparisonOrigoDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionA DBMS designed for efficient storage of vector data and vector similarity searchesA fully ACID in-memory object graph databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelVector DBMSDocument store
Object oriented DBMS
Relational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitemilvus.ioorigodb.comsplicemachine.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationmilvus.io/­docs/­overview.mdorigodb.com/­docssplicemachine.com/­how-it-worksydb.tech/­en/­docs
DeveloperRobert Friberg et alSplice MachineYandex
Initial release20192009 infounder the name LiveDB20142019
Current release2.3.4, January 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0; commercial license available
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++, GoC#Java
Server operating systemsLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateVector, Numeric and StringUser defined using .NET types and collectionsyesyes
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.nono infocan be achieved using .NETno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnonoyesSQL-like query language (YQL)
APIs and other access methodsRESTful HTTP API.NET Client API
HTTP API
LINQ
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC++
Go
Java
JavaScript (Node.js)
Python
.NetC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnoyesyes infoJavano
Triggersnoyes infoDomain Eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoclient side managed; servers are not synchronizedShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Active-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynodepending on modelyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlRole based access control and fine grained access rightsRole based authorizationAccess rights for users, groups and roles according to SQL-standardAccess rights defined for Yandex Cloud users
More information provided by the system vendor
MilvusOrigoDBSplice MachineYDB
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
MilvusOrigoDBSplice MachineYDB
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