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DBMS > Heroic vs. IRONdb vs. RDF4J vs. Splice Machine vs. TypeDB

System Properties Comparison Heroic vs. IRONdb vs. RDF4J vs. Splice Machine vs. TypeDB

Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelTime Series DBMSTime Series DBMSRDF storeRelational DBMSGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Score0.54
Rank#255  Overall
#116  Relational DBMS
Score0.81
Rank#217  Overall
#19  Graph DBMS
#99  Relational DBMS
Websitegithub.com/­spotify/­heroicwww.circonus.com/solutions/time-series-database/rdf4j.orgsplicemachine.comtypedb.com
Technical documentationspotify.github.io/­heroicdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationsplicemachine.com/­how-it-workstypedb.com/­docs
DeveloperSpotifyCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice MachineVaticle
Initial release20142017200420142016
Current releaseV0.10.20, January 20183.1, March 20212.26.3, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license availableOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++JavaJavaJava
Server operating systemsLinuxLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyesyes
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 indexesyes infovia Elasticsearchnoyesyesyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)noyesno
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnoyes, in Luayesyes infoJavano
Triggersnonoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenoneShared Nothhing Auto-Sharding, Columnar PartitioningSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter awarenoneMulti-source replication
Source-replica replication
Multi-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnonoAccess rights for users, groups and roles according to SQL-standardyes infoat REST API level; other APIs in progress
More information provided by the system vendor
HeroicIRONdbRDF4J infoformerly known as SesameSplice MachineTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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HeroicIRONdbRDF4J infoformerly known as SesameSplice MachineTypeDB infoformerly named Grakn
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