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DBMS > EXASOL vs. Heroic vs. IRONdb vs. RDF4J vs. YugabyteDB

System Properties Comparison EXASOL vs. Heroic vs. IRONdb vs. RDF4J vs. YugabyteDB

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonHeroic  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Time 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.High-performance distributed SQL database for global, internet-scale applications. Wire compatible with PostgreSQL.
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSRDF storeRelational DBMS
Secondary database modelsDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#89  Overall
#44  Relational DBMS
Score0.27
Rank#248  Overall
#16  Time Series DBMS
Score0.06
Rank#305  Overall
#26  Time Series DBMS
Score0.39
Rank#223  Overall
#11  RDF stores
Score0.83
Rank#168  Overall
#82  Relational DBMS
Websitewww.exasol.com/­en/­productsspotify.github.io/­heroic/­#!/­indexwww.irondb.iordf4j.orgwww.yugabyte.com
Technical documentationwww.exasol.com/­en/­community/­resourcesspotify.github.io/­heroic/­#!/­docs/­overviewwww.irondb.io/­docsdocs.rdf4j.orgdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperExasolSpotifyCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.YugaByte Inc.
Initial release20002014201720042017
Current releaseV0.10.20, January 20182.0.10, January 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen 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.
Implementation languageJavaC and C++JavaC and C++
Server operating systemsLinuxLinux
OS X
Unix
Windows
Linux
OS X
Data schemeyesschema-freeschema-freeyes infoRDF Schemasdepending on used data model
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyesyes
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 indexesyesyes infovia Elasticsearchnoyesyes
SQL infoSupport of SQLyesnoSQL-like query language (Circonus Analytics Query Language: CAQL)noyes, PostgreSQL compatible
APIs and other access methods.Net
JDBC
ODBC
WebSocket
HQL (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
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
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
Java
PHP
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnoyes, in Luayesyes infosql, plpgsql, C
Triggersyesnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter awarenoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate consistency per node, eventual consistency across nodesStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infoIsolation support depends on the API usedDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardnonoyes
More information provided by the system vendor
EXASOLHeroicIRONdbRDF4J infoformerly known as SesameYugabyteDB
Specific characteristicsIRONdb is a highly available, distributed Time Series Database. It can support dozens...
» more
Competitive advantagesUnmatched Scalability IRONdb is unique among TSDBs in that it does not use a consensus...
» more
Typical application scenariosReal Systems Monitoring Monitor your systems infrastructure in real time across thousands...
» more
Key customersIRONdb serves the needs of the world's largest Time Series Database customers. One...
» more
Market metricsOnly TSDB capable of scaling to billions of metrics. Only TSDB to scale to dozens...
» more
Licensing and pricing modelsIRONdb is licensed under a subscription model based on the number of active metrics...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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EXASOLHeroicIRONdbRDF4J infoformerly known as SesameYugabyteDB
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