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DBMS > EJDB vs. Microsoft Azure Synapse Analytics vs. Milvus vs. RDFox vs. Spark SQL

System Properties Comparison EJDB vs. Microsoft Azure Synapse Analytics vs. Milvus vs. RDFox vs. Spark SQL

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparisonRDFox  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searchesHigh performance knowledge graph and semantic reasoning engineSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSVector DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#296  Overall
#44  Document stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbazure.microsoft.com/­services/­synapse-analyticsmilvus.iowww.oxfordsemantic.techspark.apache.org/­sql
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.mddocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSoftmotionsMicrosoftOxford Semantic TechnologiesApache Software Foundation
Initial release20122016201920172014
Current release2.4.4, May 20246.0, Septermber 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGPLv2commercialOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
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++C++, GoC++Scala
Server operating systemsserver-lesshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesVector, Numeric and Stringyesyes
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.nonono
Secondary indexesnoyesnono
SQL infoSupport of SQLnoyesnonoSQL-like DML and DDL statements
APIs and other access methodsin-process shared libraryADO.NET
JDBC
ODBC
RESTful HTTP APIRESTful HTTP API
SPARQL 1.1
JDBC
ODBC
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
C
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoTransact SQLnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding, horizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesreplication via a shared file systemnone
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
Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes
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.yesyesno
User concepts infoAccess controlnoyesRole based access control and fine grained access rightsRoles, resources, and access typesno
More information provided by the system vendor
EJDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusRDFoxSpark SQL
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
EJDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusRDFoxSpark SQL
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