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DBMS > Kinetica vs. Milvus vs. Spark SQL vs. SQream DB vs. Transbase

System Properties Comparison Kinetica vs. Milvus vs. Spark SQL vs. SQream DB vs. Transbase

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA DBMS designed for efficient storage of vector data and vector similarity searchesSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSVector DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.73
Rank#228  Overall
#105  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitewww.kinetica.commilvus.iospark.apache.org/­sqlsqream.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.kinetica.commilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperKineticaApache Software FoundationSQream TechnologiesTransaction Software GmbH
Initial release20122019201420171987
Current release7.1, August 20212.3.4, January 20243.5.0 ( 2.13), September 20232022.1.6, December 2022Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
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++C++, GoScalaC++, CUDA, Haskell, Java, ScalaC and C++
Server operating systemsLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
LinuxFreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesyes, ANSI Standard SQL Typesyes
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.nononono
Secondary indexesyesnononoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
.Net
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnonouser defined functions in Pythonyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesnono
User concepts infoAccess controlAccess rights for users and roles on table levelRole based access control and fine grained access rightsnofine grained access rights according to SQL-standard
More information provided by the system vendor
KineticaMilvusSpark SQLSQream DBTransbase
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
KineticaMilvusSpark SQLSQream DBTransbase
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