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

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

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  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 searchesSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelDocument storeRelational DBMSVector DBMSRelational DBMSRelational 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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbazure.microsoft.com/­services/­synapse-analyticsmilvus.iospark.apache.org/­sqlsqream.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperSoftmotionsMicrosoftApache Software FoundationSQream Technologies
Initial release20122016201920142017
Current release2.4.4, May 20243.5.0 ( 2.13), September 20232022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoGPLv2commercialOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial
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++, GoScalaC++, CUDA, Haskell, Java, Scala
Server operating systemsserver-lesshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesVector, Numeric and Stringyesyes, ANSI Standard SQL Types
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 indexesnoyesnonono
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statementsyes
APIs and other access methodsin-process shared libraryADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
.Net
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
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoTransact SQLnonouser defined functions in Python
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding, horizontal partitioningShardingyes, utilizing Spark Corehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
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-constraintsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyesyes
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.yesno
User concepts infoAccess controlnoyesRole based access control and fine grained access rightsno
More information provided by the system vendor
EJDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusSpark SQLSQream DB
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 WarehouseMilvusSpark SQLSQream DB
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