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DBMS > Milvus vs. Sequoiadb vs. Spark SQL vs. Transbase

System Properties Comparison Milvus vs. Sequoiadb vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameMilvus  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA DBMS designed for efficient storage of vector data and vector similarity searchesNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelMultivalue DBMSDocument store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.28
Rank#271  Overall
#11  Multivalue DBMS
Score0.45
Rank#245  Overall
#38  Document stores
#116  Relational DBMS
Score22.94
Rank#34  Overall
#20  Relational DBMS
Score0.22
Rank#285  Overall
#132  Relational DBMS
Websitemilvus.iowww.sequoiadb.comspark.apache.org/­sqlwww.transaction.de/­en/­solutions/­transbase-resource-optimized-high-performance-database
Technical documentationmilvus.io/­docs/­overview.mdwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­transbase-inside
DeveloperSequoiadb Ltd.Apache Software FoundationTransaction Software GmbH
Initial release2019201320141987
Current release1.0, March 20213.1.1, March 2021Transbase 8.4, September 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++ScalaC and C++
Server operating systemsLinuxLinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateNumeric data onlyyes infooid, date, timestamp, binary, regexyesyes
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 indexesnoyesnoyes
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIproprietary protocol using JSONJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC++
Go
Java
Python
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnoJavaScriptnoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoDocument is locked during a transactionnoyes
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.nononono
User concepts infoAccess controlnosimple password-based access controlnofine grained access rights according to SQL-standard

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More resources
MilvusSequoiadbSpark SQLTransbase
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