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DBMS > EXASOL vs. IRONdb vs. Milvus vs. RDF4J vs. Spark SQL

System Properties Comparison EXASOL vs. IRONdb vs. Milvus vs. RDF4J vs. Spark SQL

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonIRONdb  Xexclude from comparisonMilvus  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA DBMS designed for efficient storage of vector data and vector similarity searchesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSVector DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.exasol.comwww.circonus.com/solutions/time-series-database/milvus.iordf4j.orgspark.apache.org/­sql
Technical documentationwww.exasol.com/­resourcesdocs.circonus.com/irondb/category/getting-startedmilvus.io/­docs/­overview.mdrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation
Initial release20002017201920042014
Current releaseV0.10.20, January 20182.3.4, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0
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 and C++C++, GoJavaScala
Server operating systemsLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsVector, 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.nononono
Secondary indexesyesnonoyesno
SQL infoSupport of SQLyesSQL-like query language (Circonus Analytics Query Language: CAQL)nonoSQL-like DML and DDL statements
APIs and other access methods.Net
JDBC
ODBC
WebSocket
HTTP APIRESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languagesJava
Lua
Python
R
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes, in Luanoyesno
Triggersyesnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardnoRole based access control and fine grained access rightsnono
More information provided by the system vendor
EXASOLIRONdbMilvusRDF4J infoformerly known as SesameSpark 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...
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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...
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Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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EXASOLIRONdbMilvusRDF4J infoformerly known as SesameSpark SQL
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