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DBMS > HyperSQL vs. InfluxDB vs. RavenDB vs. Stardog

System Properties Comparison HyperSQL vs. InfluxDB vs. RavenDB vs. Stardog

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Editorial information provided by DB-Engines
NameHyperSQL infoalso known as HSQLDB  Xexclude from comparisonInfluxDB  Xexclude from comparisonRavenDB  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBDBMS for storing time series, events and metricsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSTime Series DBMSDocument storeGraph DBMS
RDF store
Secondary database modelsSpatial DBMS infowith GEO packageGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitehsqldb.orgwww.influxdata.com/­products/­influxdb-overviewravendb.netwww.stardog.com
Technical documentationhsqldb.org/­web/­hsqlDocsFrame.htmldocs.influxdata.com/­influxdbravendb.net/­docsdocs.stardog.com
DeveloperHibernating RhinosStardog-Union
Initial release2001201320102010
Current release2.7.2, June 20232.7.6, April 20245.4, July 20227.3.0, May 2020
License infoCommercial or Open SourceOpen Source infobased on BSD licenseOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoAGPL version 3, commercial license availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoC#Java
Server operating systemsAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesLinux
OS X infothrough Homebrew
Linux
macOS
Raspberry Pi
Windows
Linux
macOS
Windows
Data schemeyesschema-freeschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesNumeric data and Stringsnoyes
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 infoImport/export of XML data possible
Secondary indexesyesnoyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyesSQL-like query languageSQL-like query language (RQL)Yes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsHTTP API infoJDBC via HTTP
JDBC
ODBC
HTTP API
JSON over UDP
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesAll languages supporting JDBC/ODBC
Java
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresJava, SQLnoyesuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyesnoyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoin enterprise version onlyShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infoin enterprise version onlyMulti-source replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesnonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoDepending on used storage engineyes
User concepts infoAccess controlfine grained access rights according to SQL-standardsimple rights management via user accountsAuthorization levels configured per client per databaseAccess rights for users and roles
More information provided by the system vendor
HyperSQL infoalso known as HSQLDBInfluxDBRavenDBStardog
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
HyperSQL infoalso known as HSQLDBInfluxDBRavenDBStardog
DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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Recent citations in the news

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

provided by Google News

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