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DBMS > AgensGraph vs. Milvus vs. Spark SQL vs. YottaDB

System Properties Comparison AgensGraph vs. Milvus vs. Spark SQL vs. YottaDB

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLA 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 fast and solid embedded Key-value store
Primary database modelGraph DBMS
Relational DBMS
Vector DBMSRelational DBMSKey-value store
Secondary database modelsRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.20
Rank#317  Overall
#47  Key-value stores
Websitebitnine.net/­agensgraphmilvus.iospark.apache.org/­sqlyottadb.com
Technical documentationbitnine.net/­documentationmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmlyottadb.com/­resources/­documentation
DeveloperBitnine Global Inc.Apache Software FoundationYottaDB, LLC
Initial release2016201920142001
Current release2.1, December 20182.3.4, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPL 3.0
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++, GoScalaC
Server operating systemsLinux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Docker
Linux
Data schemedepending on used data modelyesschema-free
Typing infopredefined data types such as float or dateyesVector, 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.nononono
Secondary indexesyesnonono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsby using the Octo plugin
APIs and other access methodsCypher Query Language
JDBC
RESTful HTTP APIJDBC
ODBC
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC
Java
JavaScript
Python
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresyesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole based access control and fine grained access rightsnoUsers and groups based on OS-security mechanisms
More information provided by the system vendor
AgensGraphMilvusSpark SQLYottaDB
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
AgensGraphMilvusSpark SQLYottaDB
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