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DBMS > Apache Doris vs. EXASOL vs. Google Cloud Datastore vs. IRONdb vs. RDF4J

System Properties Comparison Apache Doris vs. EXASOL vs. Google Cloud Datastore vs. IRONdb vs. RDF4J

Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA 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.
Primary database modelRelational DBMSRelational DBMSDocument storeTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websitedoris.apache.org
github.com/­apache/­doris
www.exasol.comcloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/rdf4j.org
Technical documentationgithub.com/­apache/­doris/­wikiwww.exasol.com/­resourcescloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentation
DeveloperApache Software Foundation, originally contributed from BaiduExasolGoogleCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20172000200820172004
Current release1.2.2, February 2023V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++Java
Server operating systemsLinuxhostedLinuxLinux
OS X
Unix
Windows
Data schemeyesyesschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes, details hereyes infotext, numeric, histogramsyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLyesyesSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsJDBC
MySQL client
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesJavaJava
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsusing Google App Engineyes, in Luayes
TriggersnoyesCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using Paxosconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Apache DorisEXASOLGoogle Cloud DatastoreIRONdbRDF4J infoformerly known as Sesame
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